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abacus

The abacus is the earliest known computer. I think it was invented by designers in China, Inc. and is still widely used. When I lived in Japan in the 1980s, I often marvelled at the speed with which so many shopkeepers could tally totals with this archaic computer. The design incorporates a simple GUI, but no identifiably cybernetic features. The cost/performance ratio is still one of the best in the industry.

abacus

Keywords References
computer  algorithms    logic
cybernetics  parallel computing
probability  probability
system engineering
The Intelligent Calculator V.7 Model
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abstract

Picasso Stamp A concept, thought or object not represented by things corporeal. Abstract may also be a representation or reassembly of physical things in a manner that is one or more removes from reality, as in abstract art. Physical things we can perceive through the senses, possibly with the aid of telescopes, microscopes, dyes, etc. Abstract things are ideas that may or may not apply to physical things, but that must be linked somehow in the brain. Since much, or most of what we know is physical, there must be connections between the physical and abstract.
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abstraction

A system design feature or capability that permits both composition and decomposition (see cross-reference definitions). Abstraction is one of the most appealing characteristics of object-oriented systems in that it permits processing of objects whose characteristics may or may not be completely known at the time the system is built. Abstracted Functions
Keywords References
strata   polymorphism  context
object    existential  knowledge representation
dimension   creativity  logic
continuum   class  taxonomy
composition   decomposition
object-oriented   inheritance

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acetylcholine

Acetylcholine (ACh) neurotransmitterNeurotransmitter chemical CH3--CO--O--CH2--CH2--N--(CH3)3 acetylcholine is liberated from synaptic vesicles to propogate impulses across synapses from axons of motoneurons, and pre- and postganglionic and parasympathetic cholinergic neurons. Keywords: Amines channel neurotransmitter action potential E/I synapse cholinergic dopamine norepinephrine References: brain physiology neurons neuroscience Hotlinks: Molecular Structure V.2 Cells Transmission Agents V.3 Nets Cross Refs: acetylated
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ACID

A transaction standard for database (mostly relational) manipulation that delivers immediate consistency. ACID stands for:
  • Atomicity: Either the task (or all tasks) within a transaction are performed or none of them are. This is the all-or-none principle. If one element of a transaction fails the entire transaction fails.
  • Consistency: The transaction must meet all protocols or rules defined by the system at all times. The transaction does not violate those protocols and the database must remain in a consistent state at the beginning and end of a transaction; there are never any half-completed transactions.
  • Isolation: No transaction has access to any other transaction that is in an intermediate or unfinished state. Thus, each transaction is independent unto itself. This is required for both performance and consistency of transactions within a database.
  • Durability: Once the transaction is complete, it will persist as complete and cannot be undone; it will survive system failure, power loss and other types of system breakdowns.
(from Dataversity: http://www.dataversity.net/acid-vs-base-the-shifting-ph-of-database-transaction-processing/) Some big data standards use distributed models with BASE transactions.  
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acquisition

1. In weaponry, successfully locking onto a target. Cogs Joined2. In business finance, buying something out from underneath someone [see 1]. 3. In learning, getting knowledge. The types of knowledge we may acquire are patterns governing the use and interpretation of perceptual input including images, sounds, smells, and complex input such as language. Keywords: epistemology language natural language communication interpretation translation cognition References: cognition learning pattern recognition
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action

1) in physics, action is anything that happens, and is presumed to catalyze an equal and opposite reaction 2) in semantics, it is the intent of the verb in a sentence or phrase 3) in behavior, it is the observable result of human volition and decision, or some involuntary phenomenon semantics verb volition decision
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action potential

A Normal SpikeElectromotive potential propagated through electrochemical reactions in brief regenerative pulses along neural or muscle fibers. This electrical flow is divided into positive or excitatory impulses and negative or inhibitory impulses (E/I). The flow of action potential in the brain is chaotic. Keywords: weight spike Schwann cell resting potential relay Ranvier, nodes of quantal release pump permeability overshoot oligodendrocyte norepinephrine local potential impulse exocytosis endocytosis efferent E/I decay brain circuitry anticholinesterase afferent acetylcholine activation firing threshold chaos neuron hyperpolarization depolarization synapse neurotransmitter References: brain physiology fuzzy logic neural networks neurons neuroscience


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actionable

Useable in determining a course of action, or pointing to a specific course of action. Actionable information is close to becoming knowledge, or it's already there. From PC Magazine - actionable intelligence is: "Having the necessary information immediately available in order to deal with the situation at hand.  With regard to call centers, it refers to agents having customer history and related product data available on screen before the call is taken." data     information    knowledge
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actionable information

Focus EyeInformation that can be acted upon without further analysis. One distinction between "information" and "knowledge" is that information is characterized by associated data elements combined to add meaningfulness, while knowledge is characterized by actionability: the ability to make immediate decisions and take action without seeking additional information or performing complex analyses. As such, the intrinsic value of actionable information is the reduction in time from consumption to realization of value.
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activation

Action Potential VariationsIn this blog, activation is used in two contexts: 1) excitatory action potentials as they spread in the brain; and 2) elevated values that are applied to conceptual representations as associations are traversed in an associationist network. In both contexts, activation is capable of heating up entire areas of the network (or cortex) that contain related information. Keywords: channel asymptote action potential firing threshold chaos neuron hyperpolarization depolarization synapse neurotransmitter References: algorithms brain physiology fuzzy logic neural networks neurons probability psychology
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adaptation

GoldfinchNatural systems change through adaptation. Dr. Charles Darwin observed adaptations of Finches.  The topography of continents adapts to the flow patterns of wind and water. The link structure of the brain adapts to accommodate new ideas and knowledge. The ability to adapt or learn is needed for systems of the future to be able to perform more brain tasks. Keywords: learning exposure genetics genetic algorithms References: algorithms cybernetics fuzzy logic genetics learning neural networks
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adrenergic

SynapseDifferent kinds of neurons respond to different chemicals. Synapses (or neurons) that respond to the neurotransmitter adrenaline (epinephrine) are adrenergic. Keywords: norepinephrine neurotransmitter cholinergic neuron References: brain physiology neural networks neurons
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afferent

Brain ConnectionsAxon fibers that conduct impulses toward the brain, or within the brain toward the center of the neuron. In the computational metaphor, an afferent would be represented by an input device or channel such as a keyboard, mouse or microphone. Afferent neurons are peripheral sensory neurons that collect information from the body and transmit it toward the central nervous system. Keywords: action potential axon E/I nerve fiber input output efferent References: brain physiology neurons neuroscience
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agent

1) In commerce: one who has authority to complete transactions is the agent. 2) In process: a person or thing that is responsible for begining, catalyzing, performing or completing any action. 3) In computing: a program or chunk of code that acts without specifically being activated by a human user to begin, catalyze, perform or complete any action. Keywords: semantics cybernetics self code computing consciousness volition
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AI

Artificial Intelligence. This is the science of designing machines that perform tasks normally associated with human intelligence. AI techniques run the gamut from robot arms that can pick up screws to expert systems that diagnose illnesses and prescribe medicines. Keywords: survival robot multi-valued logic learning fuzzy frame dementia cognitive modeling ALife expert system inference robotics fuzzy logic cybernetics References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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algorithm

Algorithm in HandA process flow description. Computers run on algorithms or sets of instructions that describe the process flow in detail. The robustness of an algorithm is a measure of how well it accomplishes the purpose for which it is intended. Keywords: state space image processing ATN robust schemata problem design branching computer process heuristic causal relations References: AI programming algorithms automata computing formalisms logic rules
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ALife (Artificial Life)

Artificial Life! ALife theory takes a step beyond artificial intelligence. Rather than ask “what is intelligence and how do you imitate it with computers?" ALife asks "what is life and how do you imitate it with machines?" For ethical or theological questions raised in the science of cybernetics, ALife provides the icing on the philosophical cake. Keywords: robot MIPUS learning dementia AI cybernetics genetics survival android robotics References: AI programming cybernetics ethics genetics neural networks science fiction
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ambiguity

A universal phenomenon in perception, cognition, and communication in which the nature or meaning of a thing or a communication is not immediately apparent or could have multiple interpretations. In language, words and sentences exhibit polysemy or multiple meanings. Resolving ambiguity is called disambiguation. Keywords: word anaphora polysemy lexical disambiguation perception cognition communication context References: chaos cognition comprehension context inference information/entropy logic pattern recognition perception psychology
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amines

Another chemical that mediates chemical balance in the brain. Decrease in a class of brain chemicals called amines is correlated with depression (see cross-references below). Keywords: norepinephrine dopamine neurotransmitter acetylcholine References: brain physiology neurons neuroscience
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amnesia

Forgetting what we once remembered, often in bulk. Amnesia is usually associated with some traumatic event in which the memory-access mechanism of the brain is damaged. It doesn't typically mean that the memory has been "erased," just that one can no longer read it. There are many documented instances of total amnesia and some of total recovery. Keywords: memory learning association hypermnesia References: memory psychology
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amygdala

Part of the limbic system located adjacent to the hippocampus. The amygdala is associated with emotional expression. A linkage between the amygdala and the physical systems of the body that are activated by the amygdala in association with emotions may constitute an important part of cognition. The systems that participate in emotions may someday be determined to be part of the "Mind." Keywords: hippocampus thalamus emotion hypothalamus limbic system objective subjective References: brain physiology neuroscience
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analog

Some computers and a lot of computerized test and measuring equipment use analog circuits. Unlike digital circuits that represent everything as ones and zeros, analog circuits can represent multiple values. This makes them more desirable for some measurement tasks. Keywords: digital computing continuum representation References: algorithms automata computing logic
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analysis

Analysis Concept 1) The process of breaking apart or disassembling a thing, often abstract or intangible, for the intent of understanding it. In computing professions, analysis precedes (or should precede) design. The opposite of analysis is synthesis. Cybernetics is, by definition, synthetic. 2) The first phase in an automation project in which the business and technical requirements are gathered and formalized into a business systems analysis to serve as the basis for system design. Keywords: pragmatics parsing meaningful design descriptive relations synthesis statistical analysis probability stochastic process References: algorithms computing context fuzzy logic inference perception
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anaphora

rhetorical device that consists of repeating a sequence of words at the beginnings of neighboring clauses, thereby lending them emphasis. Keywords: ambiguity language word polysemy References: chaos comprehension fuzzy logic natural language words/morphology
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android

1) A popular science fiction term for a mechanical life form. Androids are machines with varying degrees of intelligence that serve non-mechanical intelligent life forms. 2) A mobile operating system from Google 3) A device running the android operating system Keywords: tools robotics robot MIPUS ALife cerebellum References: AI programming cybernetics ethics genetics neural networks science fiction
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ANS

Artificial Neural Systems. This is the designation for neural networks that are not biological. Keywords: neural network neuromorphism brain circuitry chaos E/I link node References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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anticholinesterase

Cholinesterase inhibitor that prolongs decay of action potential changes or spikes. If action potential decays more slowly, it will not require as strong an impulse to bring the potential of a neuron beyond the firing threshold. In other words, anticholinesterase makes excited neurons more excitable. Keywords: action potential decay spike firing threshold synapse References: brain physiology neurons neuroscience
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anxiety

A mental state motivated by fear. There appears to be a biological component of anxiety. The National Institutes of Health have identified serotonin transporter in this context. There are natural variations in transporter molecules from one person to another. Those who make more of the molecule tend to be less anxious. Those who make less tend to be more anxious. Serotonin probably constitutes only a small component of the biological basis of anxiety. Keywords: prediction objective expectations eliminativism References: chaos cognition context logic pathology psychology
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aphasia

A degraded language capability due to lesions in the cortical language areas or association pathways. Expressive aphasia affects spoken language (Broca's area) while receptive aphasia affects language interpretation and memory (Wernicke's area). Keywords: association Broca's area Wernicke's area pathology natural language tactile agnosia References: brain physiology neurons neuroscience learning pathology psychology
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API

apisApplication Programmer Interface. I define API as a predefined protocol for connecting two coded objects together for the purpose of information or process exchange. The coded objects may be of the same type, or different, and may be applications or applets, services or microservices, operating systems or solutions or embedded code that controls hardware. This is a very ambiguous term, and yet, as is common with many terms, the definitions cluster closely together. Here is a definition that focuses on programmers working inside solutions: WeboPedia Here's one that emphasizes control systems such as operating systems: PCMag Here's another that dwells on applications or solutions interacting: ReadWrite Kevin Stanton provides a definition of APIs that I think is most applicable in 2016. His definition is published at Sprout Social. “API is a precise specification written by providers of a service that programmers must follow when using that service... It describes what functionality is available, how it must be used and what formats it will accept as input or return as output. In recent years, the term API colloquially is used to describe both the specification and service itself, e.g., the Facebook Graph API.”  
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arborization

Branching Branching of nerve fibers or the actual dendrites or axons that are the branches. Arborization is one characteristic of neurons that uniquely enables them to perform cybernetic functions. Keywords: branching dendrite nerve fiber axon neurite References: brain physiology neurons neuroscience
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architecture

A master plan resulting from designing things with structure. Buildings are built from blueprints which describe the architecture in detail. Computational systems of all sizes from silicon wafers up to mainframes and supercomputers are based on a design architecture. Examples of computer architectures are RISC, CISC networked and SMP. Keywords: hypertext RISC CISC design computer parallel computing digital References: AI programming algorithms automata computing formalisms logic rules
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argument

1) A good verbal fight. 2) A parameter for a function or heuristic. The arguments are the facts of input that are applied to the rules of the function to derive the output. Keywords: arity function process heuristic References: algorithms automata computing formalisms logic rules syntax
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arity

Orders ERDArity is used in relational databases and logical propositions to describe the number of arguments a function or relation is expected to possess. Relational database arities are one-to-one, one-to-many, many-to-many and variations that include the possibility of none. Functional arities are the number of arguments or relations needed to form a complete proposition or function. See: http://logic.stanford.edu/dataintegration/chapters/chap02.html Keywords: relation function form argument References: algorithms automata computing formalisms logic rules syntax
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arousal

Webster defines arouse as: "1) to awaken from sleep; 2) to stir as to action or strong feeling; 3) to evoke (some action or feeling); excite [to arouse pity] --vi. to become aroused." In the context of cybernetics, we may be concerned with setting a computer's level of readiness to receive input, or the computer's mechanism for interpreting input based on contextual cues. Keywords: sense sensory perception consciousness attention References: cognition learning pattern recognition
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ART

Adaptive resonance theory suggests competitive models for neural network learning. The learning mechanism is flexible enough to accept new inputs and smart enough to filter out noise/irrelevant input. Self-stabilizing learning systems using ART simulate interactions between short- and long-term memory. Keywords: perceptron neural network learning filtering References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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association

1. A 1960's-70's pop band with such hits as "Windy" and "Never My Love." 2. A relationship or link between data elements that provides or increases information content and hopefully decreases entropy. 3. A process in the brain that links perceptual input with stored knowledge. Keywords: tactile agnosia somatosensory cortex semantic network relation reasoning memory Martinotti link interpretation integration hypermnesia expressiveness expression experience descriptive relations aphasia amnesia correlation connectionism Broca's area Wernicke's area References: associationism connectionism context knowledge representation logic taxonomy
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astrocyte

A type of neuroglia that forms an insulating barrier for the surface area of the brain and between parts of the brain. This barrier is important to insulate neurons from both spurious electrical potentials and other substances (such as blood and water) that could interfere with neural functions. Keywords: neurogliaform neuroglia oligodendrocyte Schwann cell myelin References: brain physiology neurons neuroscience
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asymptote

AsymptotesAn asymptotic function, common to neural networks, is a curve that approaches an intersection with a straight line on the same plane, but they never meet. An asymptotic curve (Math is Fun)
Keywords References
threshold AI programming
activation algorithms   automata
spike  computing   formalisms
E/I  logic    Rules

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ATN

An Automated Transition Network uses a grammar to parse input. It consists of a state machine that transitions from state to state based on the predictable succession of tokens in a stream of tokens that abide by strict grammar rules. Keywords: state space algorithm design grammar parsing rule References: AI programming algorithms automata computing formalisms logic rules
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ATP

Adenosine TriPhosphate is a nucleotide that carries chemical energy necessary to fuel biosynthetic reactions in cells. The third phosphate is formed as a result of the energy produced by oxidation in metabolizing foods. This phosphate can be split off by hydrolysis to release energy. Keywords: mitochondrion metabolism References: brain physiology neurons neuroscience
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attention

The process of focusing one's perceptual apparatus on a certain input stimulus or set of stimuli. Attention is often associated with sight or hearing, but one can be attentive to tactile stimuli as well as tastes or smells. In the case of NeuroPedia, selective attention is necessary to manage the flood of information. Keywords: RAS consciousness filtering perception context sense arousal References: cognition learning pattern recognition
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automata

Plural of "automaton." Automata theory involves study of things that can move or act for themselves. At the most basic level, cybernetics is the study of automata whose characteristics mimic or match those of human cognition or the human brain. Keywords: GUI methodology cybernetics computing data processing mechanical brain References: AI programming algorithms automata computing formalisms logic rules
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automated data processing

ADP is different than manual data processing in that a machine is involved in the automated kind. Though the word manual implies "by hand", most manual data processing is done by head. These facts, and the differentiation between the approaches are key points of this blog.
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autonomic nervous system

Part of the peripheral nervous system that includes all involuntary motor nerves. Anything we do (like breathing) without deciding to do it is controlled by the ANS. Keywords: corticospinal tract cholinergic peripheral nervous system central nervous system involuntary parasympathetic References: brain physiology neurons neuroscience
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autonomous computing agents

Autonomous computing agents are self-managing computer programs, often very small with narrowly focused capabilities defined by the goals of the designers, able to automatically adapt to unpredictable changes in the information space. The information space may be in the physical world (such as agents operating in robots, vehicles, watercraft or aircraft), or in cyberspace. Some malicious bots are designed as autonomous agents, but uses can be benign and highly beneficial as well. Enterprise IT, Software as a Service and other  computing paradigms are becoming much more complex, making their management, integration, upgrade and retirement efforts significant and costly. Autonomous agents may be used to automate some of these activities or sub-tasks, and shield users and technicians from the underlying complexity.  
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autonomous land vehicle (ALV)

A wheeled (or possibly levitation) vehicle that gets around without a human (or other sentient being) driver. We've been using these in planetary research on Mars for awhile - less traffic to worry about than the Santa Monica Expressway. Google cars are pushing the envelope. Planetary Rover Posts with reference to autonomous land vehicle technology: Pattern Recognition in Two Dimensions     Understanding what we See A bit from Gizmodo on the history of ALVs in America
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axon

Afferent nerve fiber that transmits E/I through one or more synaptic termini. Axons can also receive input through axoaxonic synapses, but axons' output functions are predominant. Keywords: neurogliaform synapse soma Schwann cell Ranvier, nodes of output organelle oligodendrocyte neuron neurite myelin efferent climbing fibers arborization afferent dendrite nerve fiber neuroglia brain circuitry References: brain physiology neurons neuroscience
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axoplasm

The intracellular fluid of the axon. All the axon components within the membrane are suspended in this fluid. Transport of movable parts (such as synaptic vesicles) is facilitated by axoplasm. Keywords: intermediate filaments cytoplasm neuron microtubules References: brain physiology neurons neuroscience
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backpropagation

An algorithm that uses errors in the output (discrete differences between the correct output and the actual output) to train an artificial neural system to derive a correct output automatically. Here's an excerpt from Stanford Research Institute International:

The Backpropagation Algorithm

1.
Propagates inputs forward in the usual way, i.e.
  • All outputs are computed using sigmoid thresholding of the inner product of the corresponding weight and input vectors.
  • All outputs at stage n are connected to all the inputs at stage n+1
2.
Propagates the errors backwards by apportioning them to each unit according to the amount of this error the unit is responsible for.
We now derive the stochastic Backpropagation algorithm for the general case. The derivation is simple, but unfortunately the book-keeping is a little messy.
  • $\vec{x_j} = $ input vector for unit j (xji = ith input to the jth unit)
  • $\vec{w_j} =$ weight vector for unit j (wji = weight on xji)
  • $z_j = \vec{w_j}\cdot \vec{x_j}$, the weighted sum of inputs for unit j
  • oj = output of unit j ( $o_j = \sigma(z_j)$)
  • tj = target for unit j
  • Downstream(j) = set of units whose immediate inputs include the output of j
  • Outputs = set of output units in the final layer
Since we update after each training example, we can simplify the notation somewhat by imagining that the training set consists of exactly one example and so the error can simply be denoted by E. We want to calculate $\frac{\partial E}{\partial w_{ji}}$ for each input weight wji for each output unit j. Note first that since zj is a function of wji regardless of where in the network unit j is located,
\begin{eqnarray*}\frac{\partial E}{\partial w_{ji}} &=& \frac{\partial E}{\parti...<br /><br /><br /><br /><br />
...rtial w_{ji}} \\<br /><br /><br /><br /><br />
&=& \frac{\partial E}{\partial z_j} x_{ji}\\<br /><br /><br /><br /><br />
\end{eqnarray*}
Furthermore, $\frac{\partial E}{\partial z_j}$ is the same regardless of which input weight of unit j we are trying to update. So we denote this quantity by $\delta_j$. Consider the case when $j \in Outputs$. We know
\begin{displaymath}E = \frac{1}{2}\sum_{k \in Outputs} (t_k - \sigma(z_k))^2<br /><br /><br /><br /><br />
\end{displaymath}
Since the outputs of all units $k \ne j$ are independent of wji, we can drop the summation and consider just the contribution to E by j.
\begin{eqnarray*}\delta_j = \frac{\partial E}{\partial z_j} &=& \frac{\partial }...<br /><br /><br /><br /><br />
...o_j)(1-\sigma(z_j))\sigma(z_j)\\<br /><br /><br /><br /><br />
&=& -(t_j - o_j)(1-o_j)o_j\\<br /><br /><br /><br /><br />
\end{eqnarray*}
Thus
 \begin{displaymath}<br /><br /><br /><br /><br />
\Delta w_{ji} = -\eta \frac{\partial E}{\partial w_ij} = \eta \delta_j x_{ji}<br /><br /><br /><br /><br />
\end{displaymath} (17)
Stanford Research Institute International Now consider the case when j is a hidden unit. Like before, we make the following two important observations.
1. For each unit k downstream from jzk is a function of zj
2. The contribution to error by all units $l \ne j$ in the same layer as j is independent of wji
We want to calculate $\frac{\partial E}{\partial w_{ji}}$ for each input weight wji for each hidden unit j. Note that wji influences just zj which influences oj which influences $z_k \forall k \in<br /><br /><br /><br /><br />
Downstream(j)$ each of which influence E. So we can write
\begin{eqnarray*}\frac{\partial E}{\partial w_{ji}} &=& \sum_{k \in Downstream(j...<br /><br /><br /><br /><br />
...al o_j} \cdot<br /><br /><br /><br /><br />
\frac{\partial o_j}{\partial z_j} \cdot x_{ji}\\<br /><br /><br /><br /><br />
\end{eqnarray*}
Again note that all the terms except xji in the above product are the same regardless of which input weight of unit j we are trying to update. Like before, we denote this common quantity by $\delta_j$. Also note that $\frac{\partial E}{\partial z_k} = \delta_k$$\frac{\partial z_k}{\partial o_j} =<br /><br /><br /><br /><br />
w_{kj}$ and $\frac{\partial o_j}{\partial z_j} = o_j (1-o_j)$. Substituting,
\begin{eqnarray*}\delta_j &=& \sum_{k \in Downstream(j)}<br /><br /><br /><br /><br />
\frac{\partial E}{\par...<br /><br /><br /><br /><br />
...<br /><br /><br /><br /><br />
&=& \sum_{k \in Downstream(j)} \delta_k w_{kj} o_j (1-o_j)\\<br /><br /><br /><br /><br />
\end{eqnarray*}
Thus,
 \begin{displaymath}<br /><br /><br /><br /><br />
\delta_k = o_j (1-o_j) \sum_{k \in Downstream(j)} \delta_k w_{kj}<br /><br /><br /><br /><br />
\end{displaymath} (18)
Stanford Research Institute International We are now in a position to state the Backpropagation algorithm formally. Formal statement of the algorithm: Stochastic Backpropagation(training examples, $\eta$ninhno) Each training example is of the form $\langle \vec{x}, \vec{t}<br /><br /><br /><br /><br />
\rangle$ where $\vec{x}$ is the input vector and $\vec{t}$ is the target vector. $\eta$ is the learning rate (e.g., .05). ninh and no are the number of input, hidden and output nodes respectively. Input from unit i to unit j is denoted xji and its weight is denoted by wji.
  • Create a feed-forward network with ni inputs, nh hidden units, and no output units.
  • Initialize all the weights to small random values (e.g., between -.05 and .05)
  • Until termination condition is met, Do
    • For each training example $\langle \vec{x}, \vec{t}<br /><br /><br /><br /><br />
\rangle$, Do
      1. Input the instance $\vec{x}$ and compute the output ou of every unit.
      2. For each output unit k, calculate
      \begin{displaymath}\delta_k = o_k(1-o_k)(t_k - o_k)<br /><br /><br /><br /><br />
\end{displaymath}
      3. For each hidden unit h, calculate
      \begin{displaymath}\delta_h = o_h(1-o_h)\sum_{k \in Downstream(h)} w_{kh}\delta_k<br /><br /><br /><br /><br />
\end{displaymath}
      4. Update each network weight wji as follows:
      \begin{eqnarray*}w_{ji} &\leftarrow& w_{ji} + \Delta w_{ji}\\<br /><br /><br /><br /><br />
{\rm where} \quad \Delta w_{ji} &=& \eta \delta_j x_ji\\<br /><br /><br /><br /><br />
\end{eqnarray*}

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BASE

A transaction standard for database (mostly big data) manipulation that delivers eventual consistency. BASE stands for:
  • Basically Available: This constraint states that the system does guarantee the availability of the data as regards CAP Theorem; there will be a response to any request. But, that response could still be ‘failure’ to obtain the requested data or the data may be in an inconsistent or changing state, much like waiting for a check to clear in your bank account.
  • Soft state: The state of the system could change over time, so even during times without input there may be changes going on due to ‘eventual consistency,’ thus the state of the system is always ‘soft.’
  • Eventual consistency: The system will eventually become consistent once it stops receiving input. The data will propagate to everywhere it should sooner or later, but the system will continue to receive input and is not checking the consistency of every transaction before it moves onto the next one. Werner Vogel’s article “Eventually Consistent - Revisited” covers this topic is much greater detail.
(from Dataversity: http://www.dataversity.net/acid-vs-base-the-shifting-ph-of-database-transaction-processing/) Ccompare with ACID transactions common among relational databases.  
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basket cells

A type of neuron found in the cerebellum and cerebrum. The name comes from this type of cell's characteristic tendency to spread out horizontally and straddle cells such as Purkinje cells in the cerebellum. Keywords:Purkinje neurogliaform fusiform cells cerebellum stellate cells horizontal cells References: brain physiology neurons neuroscience
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Bayes' Theorem

University of EdinburghBayes' Theorem is a mathematical equation for calculating evidence-based probability.  Reverend Thomas Bayes, University of Edinburgh (1701-1761) described how the probability (P) of a specific theoretical (T) outcome is affected by a new piece of evidence (E). The beauty of this theory and its use in conceptual networks is that it does not limit the number of constraints you can apply to solving a problem or obtaining an outcome. (There's no surviving likeness of the man) Bayes EquationTrinity Mathematical Formulas from Wolfram Better Explained Bayesian Network probability inference constraint
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Bayesian Network

Bayesian NetworkA Bayesian Network is a formalized linked collection of named nodes with propositional links used in classical multivariate probabalistic systems to predict outcomes. These networks are used and  studied in fields such as statistics, systems engineering, information theory, pattern recognition and statistical mechanics. Murphy, K. at UBC Bayesian Theorem probability chaos inference
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behavior

The way things and people act and the study of the same. Some scientists believe that the best or most important things you can learn about things and people are only relevant in the context of behavior. Empiricists tend to put a lot of stock in behavior. A balanced perspective considers behavior an important property, but does not discount experimental or structural knowledge about other properties of the thing or person. Keywords: phrenology rule fact common sense function cognition empiricism modeling References: chaos cognition ethics genetics learning pattern recognition
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belief

A mental state of acceptance that falls short of knowledge. Typically, belief would be based on evidence that is less scientifically and more emotionally satisfying. Belief factors or confidence factors are used in fuzzy reasoning. Keywords: confidence fuzzy fuzzy logic References: chaos context ethics fuzzy logic inference knowledge learning philosophy
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Big Data

Beyond relational database management systems (RDBMS), online analytical processing (OLAP) and advanced business intelligence (BI), humanity has finally evolved to a technology that doesn't need an acronym: Big Data. Instead, we choose names of children's toys (HADOOP the toy elephant) and confusing word munges (MapReduce) to describe the best new thing in high-performance data access. Big Data not only avoids the pain of endless joins between relational tables that drag most systems to their metaphorical knees, it also provides a single, elegant mechanism for accessing both structured and unstructured data. This is a key to the final answer.
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binding

1. The chemical process of building molecules by adding atoms. 2. The perceptual process of combining perceived features and patterns (such as lines, shapes and colors from an image) to develop a composite representation of the entire set of stimuli. 3. The association of variables with values in programming 4. Part of the Understanding Context blog that is least likely to break. Keywords: perception pattern stimulus recognition References: AI programming algorithms automata computing formalisms logic rules
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blackboard

1. An expert-system processing model in which diverse knowledge from diverse sources is assembled using a consistent data representation and processed in turn to form hypotheses, test them, and derive a solution. 2. A writing surface, historically often mounted on the wall of a classroom for use as a writing surface for chalk - predecessor of whiteboards Keywords: expert system References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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boundaries

The outer limits. In object-oriented methodologies, we speak of objects with properties. Boundaries are convenient properties in that they help us understand where an object fits in the space-time continuum. Keywords: polymorphism object property References: algorithms automata computing formalisms logic rules syntax
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BPM

Computer Program FlowBusiness Process Modeling: Application development methods based on process flow-diagramming that can effectively be automated using high Speed, low code tools and standards including BPMN 2.0 (BPM Notation) and BPEL (Business Process Execution Language). Gartner says: "Business process management (BPM) is a discipline that uses various methods to discover, model, analyze, measure, improve, and optimize business processes.  A business process coordinates the behavior of people, systems, information, and things to produce business outcomes in support of a business strategy. Processes can be structured and repeatable or unstructured and variable. Though not required, technologies are often used with BPM. BPM is key to align IT/OT investments to business strategy (http://www.gartner.com/it-glossary/business-process-management-bpm/).
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brain

1. A person whose intelligence is disproportionate to other aspects of his/her personality; 2. A gelatin-like organ found in most advanced organisms. Its functions and properties are not yet well understood. Keywords: spinal cord software physiology pathology organism NeuroPedia neuroanatomy mind mamillary bodies intelligence dualism cytoarchitecture cybernetics computer cognition Brodmann central nervous system cerebrum cerebellum References: brain physiology neurons neuroscience
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brain circuitry

The electrical wire is a metaphor for the way axons and dendrites transmit electrical potential. Synapses act as gates or repeaters. There may also be cell components (such as filaments) that change electrical flow characteristics in meaningful ways. These components make up cognitive circuitry. Keywords: specialization cytoarchitecture axon ANS nerve fiber synapse action potential E/I References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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brain development

The growth and maturation of the brain, in-utero and post-partum, involves cell division or mitosis in which neurons specialize for the functions they are to perform and the areas in the brain in which they are to reside. Keywords: mitosis neurite cell References: brain physiology neurons neuroscience
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brain stem

The brain stem connects the cerebrum with the cerebellum and the spinal cord. It is the area of the brain that helps regulate involuntary functions of the body (visceral and facial) and cognitive motor skills (skills that require thinking, like typing). The brain stem shares many functions with its neighbor to the south, the spinal cord. Keywords: RAS pons medulla corticospinal tract spinal cord References: brain physiology neurons neuroscience
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branching

What neurons do with their fibers and what computers do with their instructions. Arborization is a term for nerve fibers that become tree-like. Conditional statements bring about branching in computer code: if x = true, then perform the left set of instructions else, perform the right set of instructions end. Keywords: arborization algorithm process decision References: AI programming algorithms automata computing formalisms logic neurons rules
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Broca's area

Broca's area is the expressive speech area. It is where we translate our knowledge of language into understandable words and sentences. When it is injured, a person can often understand everything heard but may no longer be able to speak clearly or understandably. Keywords: natural language association Wernicke's area aphasia References: brain physiology neurons neuroscience natural language
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Brodmann

A curious guy who lived around the turn of the century who stuck electrodes into living people's heads to find out where electrical activity occurred when they did things. The results of his research are cytorarchitectural maps with the areas numbered. The numbered areas are called Brodmann's area # ... Keywords: physiology cytoarchitecture specialization brain References: brain physiology neurons neuroscience
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business intelligence

Rubics CubeMulti-dimensional analytics in business modeling and reporting has an assumed name: business intelligence (BI). A relational database is basically two dimensional with tables and columns in one dimension and primary and foreign keys in another. Multi-dimensional analytics involve "cubes" and "star schemas" that create formal edges binding together different dimensions. Each dimension is defined as a semantic concept with a set of attributes and facts. This muti-dimensionality empowers business analysts with better insights as it permits deeper analytics, advanced filtering and sorting and a variety of views that answer more complex questions than typical reports. Webopedia on BI data Big Data  
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C/S

1) A common form of tear-gas used by the United States Army in chemical warfare. 2) Client/Server: a paradigm for distributed system design in which there is a hierarchy of computing responsibility. A server is responsible for computing on behalf of multiple clients. A client performs some of its own computing and stores some of its own data, but shared data used by a client resides on a server. Keywords: computer data processing distributed References: AI programming algorithms automata computing formalisms logic rules
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canonical model

Canon in MonacoCanonical models are logical level semantic graphs, and can be used for both data and processes. "Canonical" implies a top-level prescribed set of rules that define orderliness and, when adhered to, oppose chaos. A canonical data model (CDM) defines the core content entities associated with a specific domain, their semantic meanings, attributes, and associations with other elements. A canonical process model describes top-level processes and sequences needed to comply and to accomplish a mission. Both canonical data and process models serve as reference models, forming abstract, general frameworks to support specific implementations.

Rajsky 2008
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categorize

When we generalize in the learning process we often place a new thing or concept in a hierarchy along with other like things. For example, when we see an automobile we have never seen before, we might categorize it along with other like automobiles, say, as a sporty model or as a European style. When we lump things together in categories (or classes in object-oriented systems), they can inherit characteristics of other things of the same class (for example FAST and TOO EXPENSIVE FOR ME). Keywords: taxonomy linear discrimination generalization hierarchical relations object object-oriented inheritance References: context knowledge representation logic taxonomy
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causal relation

One method of defining knowledge is to represent cause and effect as related entities. A causal relation links causes to effects in an understandable way, such as is done in a logical theorem (e.g. if it rains, then plants will grow). Keywords: relation modus tollens modus ponens interaction experience existential common sense algorithm hierarchical relations knowledge logical form References: algorithms associationism learning logic rules taxonomy
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cell

1. A small room or cubicle in a prison or convent. 2. in biology, a very small protoplasmic structure usually, with a nucleus, some filamentous and reticular masses inside, and membrane on the outside. A neuron is a cell. Keywords: neurite brain development neuron mitosis cytoplasm References: brain physiology neurons neuroscience
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central nervous system

The brain and the spinal cord. This is where we think, integrate, and process perceptual input. The brain also acts as a correlating center for information and a control center for the peripheral nervous system and autonomic nervous system. Keywords: neuroanatomy hippocampus brain peripheral nervous system autonomic nervous system parasympathetic References: brain physiology neurons neuroscience
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Central Processing Unit (CPU)

Brain Chip Computers, and other digital devices like phones and tablets, are built around central processing units (CPUs) and other components that involve computer chips or chipsets. These guys perform most of the computational heavy lifting, so they are like the brains of computers.
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cerebellum

The part of the brain associated with motor activities of the body. Robots (or androids) model the cognitive activities performed in the cerebellum in their transport systems and moving arms and hands. Keywords: stellate cells robot Purkinje mossy fibers metencephalon granule cells Golgi cells climbing fibers basket cells android brain cerebrum References: brain physiology neurons neuroscience
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cerebrum

The largest part of the central nervous system, the cerebrum, often called the cortex, may be thought of as the center of thought. Most advanced cognitive functions, including perceptual processing of sights, sounds, and other sensory input, are performed partly, if not mostly, in the cerebrum. Keywords: stellate cells pyramidal cells neurogliaform Martinotti horizontal cells fusiform cells brain morphology cerebellum cortex References: brain physiology neurons neuroscience
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certainty

A person's level of credibility or reliability associated with a specific proposition or piece of information. Keywords: confidence information entropy References: formalisms fuzzy logic genetics logic rules
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channel

A pore-like opening in synaptic membrane that permits diffusion of ions. This is a pivotal role in the propagation of E/I in the electro-chemical processes associated with cognition. Keywords: synapse acetylcholine E/I activation References: brain physiology neurons neuroscience
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chaos

Behavior of compound and/or complex elements that appears random and unpredictable. Water rushing over rapids and turbulent storm clouds are chaotic. There is no apparent order, but the result is predictable and describable. Flow of electricity in the brain is chaotic, but it usually works! Keywords: fuzzy logic symmetry self-similarity random probability neuroanatomy E/I dimension dichotomous logic determinism dead man's hand continuum connectionism combinatorial explosion ANS activation action potential multi-valued logic fuzzy cognition non-determinism MIPUS References: AI programming algorithms chaos fuzzy logic pattern recognition
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cholinergic

Neurons releasing acetylcholine (ACh) as the neurotransmitter. Cholinergic fibers (the most common) are those that form junctions between pre- and postganglionic fibers, and between parasympathetic postganglionic neurons and effector organs. Keywords: neurotransmitter acetylcholine adrenergic autonomic nervous system References: brain physiology neurons neuroscience
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CISC

Complex Instruction Set Computer design involves microprocessors with complex instruction sets. The instructions are longer and slower than RISC, but they are so common as to be needed to run most common types of programs; they are thus considered a reasonable trade-off in microprocessor design. Keywords: RISC architecture References: AI programming algorithms automata computing formalisms logic rules
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citizen developer

Less technical people, usually not in IT, who can make meaningful changes to automated capabilities. This may involve iBPM or PaaS systems that permit "low code" or even configuration only changes that modify system behaviors. Gartner IT Glossary defines it as: "A citizen developer is a user who creates new business applications for consumption by others using development and runtime environments sanctioned by corporate IT. In the past, end-user application development has typically been limited to single-user or workgroup solutions built with tools like Microsoft Excel and Access. However, today, end users can build departmental, enterprise and even public applications using shared services, fourth-generation language (4GL)-style development platforms and cloud computing services."
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class

Socioeconomic level in a stratified society. A place to study or the grouping of co-students therein. Also, in object-oriented system design, a category or grouping of objects that share certain characteristics. Keywords: taxonomy polymorphism object object-oriented composition inheritance decomposition abstraction References: algorithms automata computing formalisms logic taxonomy
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classification

In learning we generalize, that is, associate new things with known things. Generalization and its correlate, specification, form the essence of the process of classification: "placing all things in an understandable context". Classification creates hierarchies or taxonomies. This illustration shows a hierarchy.

Class Subclass Instance

If the class is "animals," for example, the tier of circles underneath animals might be dogs and cats. The next level down might be another subclass, such as breeds of dogs and cats, and or it may be specific instances, such as Fido the mutt and Fluffy the longhaired cat. learning association  generalization
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climbing fibers

One of the two types of afferent fibers (axons) that enter the cerebellum (see also mossy fiber). Climbing fibers wind among Purkinje cell dendrites, thus providing direct input to the only cerebellum cells with direct output. Keywords: mossy fibers Purkinje cerebellum axon References: brain physiology neurons neuroscience
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Code

Cryptographers create, use and break codes used to disguise communications by putting the communications in cryptic form that only certain other people can interpret. Programmers create, use and break code used to control computers by putting instructions in cryptic form that only computers can interpret. Code is what runs computers today. Keywords: data-driven data type program function modularity process input output object-oriented References: AI programming algorithms automata computing formalisms logic rules
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cognition

Advanced intellectual processing of information. Thinking. Considering. Processing data with the brain. Cognitive processes include tasks performed by most organisms, such as perception, and tasks apparently performed only by humans, such as reasoning. Keywords: time thought taxonomy symbol subjective specialization space software sense receptive field psychology prediction polysemy objective neurocomputing natural language logic linguistics language intuition intelligence innate inference implicit representation imagination gnostic emotion disambiguation dementia decision cue context conceptual concept communication chaos behavior acquisition perception think brain ambiguity cognitive modeling References: cognition learning pattern recognition
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cognitive computing

A redux of artificial intelligence (AI) for the twenty teens. Cognitive computing, or CC, systems simulate human brain tasks or thought processes in software based on a cybernetic model. CC systems may involve machine-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain processes meaning.
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cognitive modeling

The process of using some mechanism to represent or imitate cognitive processes (thinking). Building mechanical brains is the ultimate extension of cognitive modeling. Keywords: AI cognition modeling References: cognition learning pattern recognition
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Cognitive Science

The study of perception, recognition, thinking and other processes of the human brain. Keywords: eliminativism cybernetics References: cognition learning pattern recognition
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combinatorial explosion

When numbers increase exponentially, a small exponent can produce astronomical results. A classic story tells of an emperor who promised the peasant who rescued his daughter anything he wished. The peasant asked for a checkerboard with a penny on the first square, two on the next, and doubling amounts for each successive square. The naive emperor thought that was a reasonable, though unusual request, until... Keywords: chaos equation data References: algorithms automata computing logic
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combinatorial explosion

The paradox of choices is a fundamental problem in computational search and problem solving. As the number of possible constraint or solution combinations that one has to examine grows exponentially, even the fastest computers may require excessive amounts of time to deliver acceptable results. This effectively limits a system's ability to solve large problems. As it is, many problems of real interest to us have either a large number of constraints or possible solutions. Traditional "brute-force" searches where each option is compared consume processor time incrementally for each additional option. After a certain number of options, you would simply run out of time. As an example, if you have n constraints or factors for a decision, each with 10 possible options, then you will have all together 10 to the power n combinations of results. The number of combinations grows exponentially as n increases. In chess, a system could examine every possible move and the possible moves that could follow. However, if we limit it to 20 choices per move, then looking ahead 15 moves would require the system to compare 20 to the 15th power, or 3.3x10^19, sequences. If the system manages to examine 1 Billion sequences per second, a brute force search would have to take over 90 million hours or over 10,000 years to make one move. To improve the speed of play, one needs either much faster computers or heuristic algorithms that do not perform exhaustive search but choose which sequences to examine. The combinatorial explosion problem prevented computers from competing with human world champions until suitable heuristic solutions were invented.  
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common sense

A form of knowledge that associates causes with effects. Common sense typically addresses things that occur frequently enough in most people's lives to be part of a general body shared by the human family or by all members of a given culture or area. Common sense may differ in different cultures or areas so it is somewhat context-dependent. Common sense is often an important part of human decisions and behavior. Often it is not. Keywords: knowledge causal relations behavior decision learning context References: cognition comprehension inference information/entropy learning pattern recognition
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communication

A two-way process involving transmission and reception of information. Birds, bees, educated fleas and computers do it. Let's do it, too. Keywords: telecosm cyberspace polysemy linguistics expressiveness expression disambiguation acquisition language natural language interpretation translation recognition cognition ambiguity References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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composition

Composition is a technique used in object-oriented system development which involves finding general properties of like objects and grouping, categorizing, summarizing, simplifying, or abbreviating them. It is a constructive technique that permits objects in a superclass to assume certain characteristics of objects in a subclass. Keywords: range polymorphism object abstraction decomposition class object-oriented inheritance References: algorithms automata computing formalisms logic
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comprehension

This is a constructive metaphor for understanding. It bears a sense of completeness encompassing the subject. It is almost the opposite of the Japanese "wakaru," which is to separate or distinguish. Keywords: GUI understanding knowledge entropy interpretation perception References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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computational linguistics

The black art of teaching intransigent machines how to interpret, translate, summarize and recombine human language in a way that preserves the original intent. Some tools of the computational linguistics practitioner are corpora and bi-lingual corpora, grammar rule sets, semantic case rules, morphology rules, speech recognition methods and tools, statistical modeling formulas and tools, and ontologies. Translation Symmetry  
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computer

  1. Circuit BoardA mechanical device used to automatically process data (not your brain - it's different)
  2. A Programmable Calculator
  3. A mobile phone or Pad device (iPad/Android)
  4. The thing that keeps your car, refrigerator, wristwatch and heart rhythm running
Such ubiquitous devices usually contain one or more Central Processing Units (CPUs) with the possible addition of other processors specialized in numerical, graphical or audio tasks. Arguably, the more a computerized device can do, the more the computer is just a component of the thing, like your car or household robot. Eventually the focus on computers should fade into history and we will simply have intelligent controllers and communicators that help bind us together in ever smarter ways.
Keywords References
tools AI programming
GUI algorithms
architecture automata
software computing
RAM formalisms
program logic
design rules
C/S
algorithm
abacus
cybernetics
modeling
brain

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computing

Electrical and/or mechanical methods for processing data. Computing devices, or computers, can be used for tasks as simple as calculating profit and loss or as complex as defeating intergalactic invaders. Keywords: tools SIMD MIMD image processing GUI cyberspace symbolic logic schemata modeling digital analog automata neurocomputing data processing mechanical brain References: AI programming algorithms automata computing formalisms logic rules
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concept

An idea, a knowledge fragment, a glimmer of understanding, the treatment of a perceived thing in the mind, a thing that eludes definition but that is easy to understand using intuition. A framework for creation, the intellectual foundation of all great systems and inventions. Keywords: imagination conceptual cognition conceptual graph think thought uncertainty References: cognition comprehension learning inference
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conceptual

Having to do with the storage and processing of knowledge in the human mind. Conceptual implies a foundation in concepts which may be the smallest units of knowledge or the fundamental component of thought. Keywords: cognition reasoning concept conceptual graph thought memory References: cognition comprehension context fuzzy logic inference knowledge logic perception
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conceptual graph

A knowledge representation formalism proposed by John Sowa and others that uses a complex structure similar to a semantic network to represent information for artificial-intelligence applications. Keywords: concept knowledge representation symbolic logic semantic network frame information conceptual References: algorithm cognition comprehension context formalism fuzzy logic inference knowledge logic perception
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conclusion

Resolution of a thought process or proposition. We base conclusions on logic, emotions, or both. Logic is usually sufficient for simple propositions. Emotions are often critical for paradoxical situations. The combination of logic and emotions that go into human reasoning often determine the nature or probability of different flavors of conclusions to more difficult problems such as criminal sentencing and what to eat for lunch. Keywords: proposition thought paradox decision reasoning References: algorithms computing logic rules
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confidence

Confidence in cybernetics is a measure of belief or credibility. Confidence factors constitute a continuum of possible answers that provide more robust processing possibilities than the "yes or no" dichotomy. By using confidence factors, answers that may fall within a gray area can be achieved where a dichotomous approach would actually provide wrong answers as often as not. Keywords: uncertainty certainty belief fuzzy fuzzy logic References: chaos cognition comprehension fuzzy logic information/entropy logic philosophy
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connectionism

A set of theories about the chaotic link structure in the brain and modeling it using artificial neural networks. Connectionism involves a massively parallel scheme in which the salient aspect is the link structure, and the weights (levels of electrical flow permitted over the links) are the critical component. Keywords: linear discrimination neural network chaos association References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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Connectomics

A form of neural imaging and histological techniques used to increase the resolution of neural connection maps. High-throughput connectomics applications using diffusion MRI or Three-Dimensional Electron Microscopy improve the speed and efficiency of mapping connections between neurons, normally in the human brain. Alternate applications may theoretically be used in animal brains or neuromuscular junctions. The map output a Connectomics system is called a connectome.
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consciousness

A cognitive phenomenon usually active whenever one or more of the senses is turned on. Other cognitive phenomenon derive from consciousness and may be described as "heightened states of consciousness" (such as attention). Keywords: sentient psyche self arousal mind attention sense dualism References: cognition learning pattern recognition
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constraint

C-ClampA factor that affects or limits a decision or outcome. In decision making (particularly automated), it is important to limit the problem space to a manageable number of questions whose answers influence the final outcome. However, missing important constraints in evaluating a problem can lead to skewed or incorrect or unsuitable outcomes. Constraint-based reasoning attempts to prioritize the answers to all the pertinent questions and, based on the weighted sum, arrive at a decision. Keywords: feature sample space range inference logic fuzzy logic stochastic References: algorithms automata computing formalisms logic rules syntax Posts: Generating and Qualifying Propositions Framing Formal Logic
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context

Rounded body of all thingsThe situation/environment in which cognitive (and all other) activities occur. Place, time, and all sensory inputs (i.e. anything we can perceive in our surroundings) constitute the components of context. We filter out unnecessary details and focus on meaningful details such as who and what major objects are present.
  • from Latin contextus: an assembling or putting together,
  • from contexere: to interweave more than one thing,
  • from com-: together + texere: to weave or braid
  See this example of context in understanding Keywords: extra-sensory time space self somatosensory cortex polysemy meaningful intuition interaction filtering domain disambiguation common sense attention ambiguity cue cognition hippocampus interpretation References: context knowledge representation logic taxonomy
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context-free

A finite set of symbols or variables which represent categories applied to lexical elements (terminals). Context-free grammar (CFG) is great for defining relationships between syntactic objects as exemplified by the syntax of a programming language. A CFG has a start or goal symbol, terminal symbols which represent instances of variables, and production rules which combine to eventually derive the goal. Keywords: recursive context-sensitive grammar regular References: chaos comprehension fuzzy logic natural language words/morphology
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context-sensitive

A type of grammar that is more restrictive than context-free grammar. In addition to the formal syntax of the language (structure, semantics, or meaning that is inherent in words, phrases, sentences and larger), context impacts the applicability of syntactic rules. The more context it takes to understand the syntax of the sentence and thus interpret it correctly, the more difficult it is to develop an algorithm that will provide robust interpretation. Keywords: recursive context-free regular grammar References: chaos comprehension fuzzy logic natural language words/morphology
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continuum

A series that can be represented by end-points in which the values between the ends vary so much that discreet points may be difficult to find or assign. As the points approach each end, the values are successively more like the end toward which they approach, and less like the end from which they are growing more distant. Keywords: analog abstraction chaos self-similarity random References: context knowledge representation logic taxonomy
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convergence

ConvergenceWe are experiencing two great movements toward convergence in previously separate technologies:
  1. Voice and Data Convergence in which IP telephony is enabling telephone and wireless phone communications to share the same wires and bandwidth as data communications
  2. Structured and Unstructured Content Convergence in which databases (structured data) automatically mingle with documents, videos, images and sound files to bring users richer experiences.
These movements involve dramatic technical complexity and risk, but the benefits are worth the pain. Another Great Year in Cyberspace Harmonic Convergence of Light
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correlation

A function performed by cells that does not directly involve input or output, and only indirectly supports cognitive processing. Horizontal cells in the cerebrum, for example, simply provide transit pathways for inputs to reach required destinations when the input fiber is far from the target. Keywords: reasoning integration association relay horizontal cells References: cognition learning pattern recognition
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cortex

1. Gray matter found in all major areas of the brain. 2. Abbreviation for the Cerebral Cortex. Keywords: sulcus gyrus cerebrum gray matter neuron References: brain physiology neurons neuroscience
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corticospinal tract

The pathway linking the central nervous system (cortex) with the autonomic nervous system via the spine. This tract tightly interconnects the mechanisms of perception throughout the body. Keywords: autonomic nervous system peripheral nervous system brain stem References: brain physiology neurons neuroscience
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creativity

The ability to invent or synthesize something previously unknown to the inventor. Like imagination, creativity may be a characteristic unique to humans among all creatures on Earth. Creativity is a key component of generalization which is important in learning, especially language acquisition. Keywords: self-similarity fractal imagination language learning abstraction generalization References: cognition comprehension context fuzzy logic inference knowledge logic perception
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cue

Information that aids in cognition by directing focus, attracting attention, providing additional sensory dimension (such as adding audible information to visual information), or building a contextual framework for cognition. Keywords: hypertext sentient RAS integration context perception cognition sense interpretation learning recognition intelligence input References: cognition learning pattern recognition
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cybernetics

The study/practice of modeling cognitive processes on machines. Some great thinkers have hypothesized that machines can't think, so cybernetics is often associated with science fiction. State-of-the-art Artificial Intelligence tends to prove their point. Keywords: telecosm cyberspace neuromorphism meta-knowledge mechanical brain learning automata ALife AI cognitive science modeling brain computer abacus References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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cyberspace

The universe of all cybernetic thinking, whether performed by cybernetic beings (computers and robots) or cybernetically-oriented human beings. Cyberspace is used by some to refer to the online world, particularly the connected online world comprising commercial online services and the internet. The hottest thing in cyberspace at the time of this publication is the world-wide-web, an appendage of the internet that runs on HTML and plenty of JAVA. Keywords: cybernetics computing telecosm communication digital References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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cytoarchitecture

The structure and functional organization of the brain. Blueprints of the areas of the brain in which functional subdivisions are named or numbered are called cytoarchitectural maps. Keywords: Brodmann brain brain circuitry References: brain physiology neurons neuroscience
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cytoplasm

The fluid inside the cell body that suspends all the intracellular components and provides a medium for transport of foods and movable structures within the cell. Keywords: cell axoplasm neuron soma References: brain physiology neurons neuroscience
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cytoskeleton

The structural components of cells made up of actin filaments, intermediate filaments, and microtubules. For nerve cells with branching fibers, these filamentous components assist in the growth process and provide structure to the fibers. Keywords: nerve fiber microtubules intermediate filaments References: brain physiology neurons neuroscience
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data

The plural of datum. A datum is a linguistic or numerical symbol representing something concrete or abstract. "1" is a datum and "1, 2, 3" is data. As soon as links are added, such as "400, 2000 , 3505" = "daily sales for Jan 1-3," the data becomes information. Information and data are often mistakenly thought to be synonyms. Keywords: combinatorial explosion forget flip-flop information data-driven data type data processing input References: AI programming algorithms automata computing formalisms logic rules
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data processing

Data processing usually refers to electrical or mechanical techniques used to manipulate data for consumption by humans or other machines. Of course, since we have gone to great lengths to compare computers to brains, why not turn the tables and suggest that the brain is capable of processing data? Keywords: symbolic logic flip-flop C/S automata data computing mechanical brain input References: algorithms automata computing formalisms logic rules
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data type

A word used to describe the nature or properties of a data item. Examples include: textual (character), numerical (number), temporal (date/time), financial (currency) and referential (unique ID or counter). Different types of data behave differently. You can multiply numbers and get predictable results. The results of multiplying words are absolutely unpredictable. Different types of information need different types of functions. Keywords: data-driven data function code program rule modeling References: algorithms automata computing
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data-driven

In procedural techniques, the program code determines what functions to run and what data to get. In declarative techniques that are data-driven, the data dictates what code is run and what other data is used to produce results. Keywords: data code OOPS function process data type References: algorithms automata computing formalisms
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database

ERD - Entity Relationship DiagramWhen digital information is structured in a table or tables or rows and columns, especially named columns where the name of each column describes what content appears in that column for each row. Rows are described as records, and each record is usually assigned a unique ID. Data in different tables are associated with each other based on data in one or more of the columns, often using primary and foreign keys and accessed by a common language such as Structured Query Language or SQL (SQL Keys). An RDBMS is a relational database management system provides storage management and functionality needed to efficiently index, access and transact data (CRUD is Create, Read, Update and Delete). see structured content
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dead man's hand

Aces 'n' eights. Sitting in a saloon in Deadwood, Wild Bill Hickock drew a hand of aces and eights when a gun-slinger named McCall strolled in and shot him in the back. The laws of random probability considered, it is unlikely that the aces and/or eights had much to do with William's untimely demise, whereas it is statistically provable that the chances of being shot in a bar with cards in your hand are much higher than in other contexts (though lower than in Hickock's day). Keywords: probability stochastic random chaos References: chaos inference logic probability
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decay

In neuroscience, the back of an action potential curve or how long it takes the electrical potential of a neuron to return to normal after being elevated through excitation or firing. Anticholinesterase prolongs decay so that new spikes can be less intense and still force the neuron over the threshold. Keywords: action potential anticholinesterase firing spike synapse References: brain physiology neurons neuroscience
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decision

A choice, typically of a course of action, based on consideration of more than one possible option. The ability to make a decision is the hallmark of a leader and the inability to make a decision the hallmark of a lumbering bureaucracy. Keywords: objective intuition conclusion common sense branching decision support system reasoning cognition function References: cognition comprehension context fuzzy logic inference knowledge logic perception
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decision support system

Advanced computer programs that are described as "interactive computer based systems, which help decision makers utilize data and models to solve unstructured problems" [Sprague, 1986]. The key is the 'unstructured' part. DSS programs need to use robust models to capture unique and sometimes fuzzy characteristics of problems in order to help humans make better decisions. Keywords: decision expert system model base inference rule base knowledge base References: AI programming cybernetics ethics genetics neural networks
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declarative knowledge

Knowledge of objects and facts. Also called declarative memory. Includes sensory knowledge. Declarative knowledge is essential in both interpreting the external world and in introspectively placing one's self in context. Keywords: knowledge intelligence procedural knowledge episodic knowledge logic inference interpretation References: associationism cognition inference knowledge taxonomy
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declarative memory

When we think of memory, we often think of recognition, as in remembering someone's face. Memory of objects and other things that can be recognized (including aromas and textures, etc.) is called declarative. Declarative memory probably represents some of the first knowledge we acquire and the most reinforced. Keywords: short-term memory recall episodic knowledge episodic memory knowledge procedural memory memory References: associationism cognition inference knowledge memory taxonomy
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decomposition

The process of slowly returning the flesh to the dust. Also, in object-oriented system design and development, the process of analyzing and breaking a thing into its constituent parts or details. Keywords: polymorphism object granularity abstraction composition inheritance object-oriented distributed class References: algorithms automata computing formalisms logic parallel computing rules
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deductive reasoning

Understanding as convergenceDeductive reasoning takes existential and/or universal statements about knowledge, or generalizations, then uses a process similar to classification to infer specific instances or phenomena that match the pattern of the generalization. Scientific methods use deduction to test a theory beginning with a general statement, or hypothesis, and examining the possible outcomes or similarities to reach a specific, logical conclusion. Livescience on Deductive vs. Inductive reasoning
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deixis

Words and phrases that cannot be fully understood without additional contextual information. Resolving deixis requires cues from semantic and syntactic, as well as prosody, and possibly other elements in language. pragmatics
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dementia

In former usage, dementia meant madness or insanity. Now it is usually used to describe impairment or loss of cognitive or mental abilities due to disease process. Dementia is distinguished from amentia – severe congenital cognitive deficiency. It is important to study pathologies so as to avoid designing machines that are susceptible to antisocial pathological behaviors. Keywords: pathology cognition AI ALife References: brain physiology neurons neuroscience learning pathology psychology
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dendrite

Receptor nerve fibers. Input of electrical impulses come into neurons through synapses in dendrites. Dendrites are not the only source of neural input because input synapses come into cell bodies as well as axons. Keywords: synapse soma organelle neuron gray matter arborization neurite axon nerve fiber References: brain physiology neurons neuroscience
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depolarization

Reduction in the negative resting potential of neurons caused by excitation. Keywords: E/I activation action potential hyperpolarization threshold References: brain physiology neurons neuroscience
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descriptive relation

A kind of relation in which characteristics are ascribed to a thing. Also called ascriptive relation, the thing may be a real physical thing like a robot or an abstract thing like a theory. We might ascribe the 'smart' property to the robot and the 'dumb' property to the theory. When we generalize and categorize, descriptive relations or properties are often inherited down the hierarchy. Keywords: property existential hierarchical relations inheritance learning link analysis association explicit representation discriminate References: associationism cognition inference knowledge taxonomy
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design

1) The form, function and structure of a thing (its design) 2) A grand plan 3) The second phase of an automation project. After the completion of analysis, the design phase is a creative process of creating a model to automate the solution to business requirements. Design comes after analysis and before the build phase in which the design is realized in an actual system. Keywords: tools ATN architecture analysis program computer algorithm process References: AI programming algorithms automata computing formalisms logic rules
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determinism

Producing a predictable outcome. Deterministic programs branch – that is, decide among possible choices on what to do next – based on absolute conditions. Determinism usually applies dichotomies or logic to test variables against conditions to control program flow and produce desired results. The more data-driven programming techniques, the less predictable the results. Keywords: modus tollens modus ponens exception non-determinism dichotomous logic fuzzy logic logic chaos grammar References: cognition comprehension context fuzzy logic inference knowledge logic perception
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DevOps

A new discipline in information technology implementation and support that infuses an organization with big-picture thinking and cross-functional collaboration in building, testing, maintaining, upgrading and repairing information technologies to speed up software release and repair cycles while improving quality. DevOps Site DevOps Revolution Manifesto The Three Ways
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dichotomous logic

A method of reasoning based on the assumption that each constraint in the problem can be judged to be true or false. The true/false dichotomy, when applied to each constraint in the problem, provides bases for branching in decision trees. Aristotle was a proponent of two-valued logic. The mathematics of two-valued logic served as the core of most control structures in programming languages for many years. Keywords: multi-valued logic modus tollens modus ponens fuzzy flip-flop determinism non-determinism fuzzy logic logic chaos grammar References: algorithms automata computing formalisms logic rules
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diencephalon

The area of the brain associated with sensory integration, among other things. Keywords: sense integration thalamus hypothalamus References: brain physiology neurons neuroscience
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differentiation

Part of the biological growth process of organisms involves a process of cell division (mitosis) in which daughter cells assume different form/function than the parent cell. If not for differentiation, complex life forms could not exist. DNA provides the information necessary for differentiation. Keywords: neuron DNA mitosis References: associationism cognition inference knowledge taxonomy
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digital

Most computers use digital circuits. That means that each register in the machine is capable of representing exactly two states: 0 or 1. Using many zeros and ones, you can represent integers in base 2 or binary code. You can use numbers to represent letters or abstract formulae. Digital computers use zeros and ones for everything. Keywords: telecosm cyberspace architecture flip-flop analog computing representation References: algorithms automata computing formalisms logic rules
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digital consumability

digital-owl-3Consumability is predictably ambiguous. IBM uses the term to mean "assets available on machines in a LoadLeveler® cluster." but consumability means "a client's complete experience with a technology solution beginning with buying the right product to updating it." This is not what I'm talking about. Digital consumability, in the context of this blog, is a property of digital information involving formats accessible to multiple systems and processes (such as heuristics) that may benefit from it. This means that systems that didn't create it and don't manage it can get it and use it to bring some value. Many Legacy computing systems are unable to adapt their behavior based on consuming external data. But as more "services", micro-services, and cognitive computing systems arise in an IT ecosystem where API's facilitate interconnections between systems, the importance of rich consumable digital information increases, and creates opportunities to add intelligence to existing processes.
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dimension

In physical space, a dimension refers to an abstract measure of direction. The first dimension may be described as length: a straight line has distance and direction. The second dimension is width. With these two dimensions we can create geometrical representations of information. The bell curve is a two-dimensional representation. The third dimension is depth. All objects in the physical universe have three dimensions. Other dimensions are duration and speed. Keywords: abstraction object chaos representation References: context knowledge representation logic taxonomy
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disambiguation

The process of resolving polysemy or other forms of ambiguity. Linguistic ambiguity arises from polysemy. Sensory ambiguity arises from physical and physiological obstacles to clear perception. Extreme cold may seem to burn a person's skin. Shadows in the darkness may play tricks on a person's eyes. We use context heavily to help us disambiguate input, whether perceptual or linguistic. Keywords: context ambiguity polysemy perception cognition communication References: chaos comprehension fuzzy logic natural language words/morphology
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discern

To separate one thing from another in the mind or to recognize clearly. The Japanese word "wakaru" is usually interpreted as "to understand" but its roots really mean to discern. The first meaning of discern is much like the meaning of discriminate. Keywords: discriminate mind recognition interpretation knowledge understanding reasoning References: associationism cognition inference knowledge taxonomy
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discriminate

Discrimination has negative connotations, but it is one of the most fundamental cognitive processes in humans. It means to clearly distinguish or recognize a perceived or conceptual thing, and separate what it is from what it is not. Keywords: descriptive relations discern knowledge understanding symbol References: associationism cognition inference knowledge taxonomy
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distributed

The opposite of centralized. Instead of everything going into one whole mass of something, it goes out to a bunch of separate somethings. The underlying philosophy is to divide and conquer. Distributed models are good for computing and running nations. Keywords: hypertext C/S decomposition parallel computing neural network formalism modeling References: algorithms automata computing formalisms logic rules
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DNA

DNA (deoxyribonucleic acid) is a basic component of genetic information transfer. Biological information that determines the form and function of cells, tissues, organs and organisms is encoded in DNA's double helical strands. (See RNA.) Keywords: zygote RNA genetics genetic algorithms differentiation heredity References: brain physiology neurons neuroscience
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domain

A context. Within a domain or context facts and rules typically interact in consistent ways. Once you leave the narrow confines of a domain, the interaction of facts and rules can be irratic or ambiguous. Within a domain inference mechanisms can be designed to favor domain-specific interpretations of facts and rules. Keywords: time space sample space problem interaction rule fact context expert system inference References: context knowledge representation logic taxonomy
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dopamine

A tyrosine-derived inhibitory neurotransmitter chemical found in the basal ganglia and corpus striatum. Dopamine deficiency is linked to Parkinson's Disease. Loss or lack of dopamine in nigro-striatal neurons in the center of the brain is what causes the muscles to not operate as directed by those who suffer from Parkinson's disease. Some studies also link a tendency toward alcoholism to dopamine. Keywords: norepinephrine acetylcholine E/I amines neurotransmitter acetylcholine References: brain physiology neurons neuroscience
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dualism

A school of thought that suggests a distinction between the mind and the brain. This may be a relevant question if the mechanism of consciousness includes organs beyond the cortex. One argument of proponents is that the sense of self associated with perception and cognition may be something that either is not or cannot be contained in the brain alone. Keywords: brain mind consciousness psyche References: cognition comprehension context fuzzy logic inference knowledge logic perception
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E/I

Excitatory (positive) and Inhibitory (negative) changes in action potential. Excitatory changes lead to a neuron firing or becoming activated while inhibitory influences reduce the activation. Resting potential is the absence of excitation or inhibition. Keywords: weight threshold synaptic vesicle relay Ranvier, nodes of quantal release pump overshoot norepinephrine local potential impulse firing exocytosis endocytosis efferent dopamine channel brain circuitry asymptote ANS afferent acetylcholine action potential resting potential depolarization hyperpolarization neurotransmitter chaos References: brain physiology neurons neuroscience
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eclecticism

Research or other pursuit that incorporates the knowledge of many different academic disciplines. Cognitive science is eclectic because it incorporates knowledge from human physiology, psychology, computer science, anthropology, philosophy, and other fields. References: cognition fuzzy logic inference knowledge logic
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efferent

Axon fibers that conduct impulses away from the cerebral cortex. In the computational metaphor, an efferent would be represented by an output channel. Keywords: afferent action potential axon E/I nerve fiber input output References: brain physiology neurons neuroscience
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Electrical Current

The source of electrical power derived from electrons breaking free and being recaptured. The passing of electrons between atoms in an element or substance causes electrical current. Remember that electrons revolve around the positively attractive nucleus in orbits at various distances. Centripetal force constantly tugs at the electrons, pulling against the attraction of the nucleus. This gives these smaller particles a tendency to detach from the atom. But the attraction force between negative electrons and positive nucleus is normally strong enough to keep them bounded in the atomic orbit. The centripetal force tugging at the electrons increases at greater distances of the electrons’ orbit from the nucleus, and magnetic force between electrons and nucleus weakens. The attraction further weakens for electrons in outer orbits because of a repulsion force from other electrons in inner cells. That explains why electrons in outer most orbit are most loosely bonded with the nucleus and vulnerable to detachment. For some elements and substances, the outermost electrons are so loosely bonded that very little force is needed to detach them from their parent atom. Atoms in their normal state are electrically neutral as they possess an equal number of positive protons and negative electrons, creating balance. But escaping electrons create imbalance, and until the atoms thus deprived can grab a free atom from somewhere, the stable number of protons make the atoms become positively charged. After detaching from parent atoms, electrons move about freely, attracted by whatever force intersects their inertial trajectory. Other positively charged atoms in the vicinity opportunistically   pull in free electrons. In general, the outermost electrons in metal atoms are very loosely bonded, so free electrons are always available in metal, which makes the metal a good conductor of electric current. Water molecules, which constitute a significant portion of the human body, are also very good conductors. Learn about Electricity
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eliminativism

A school of thought in cognitive psychology in which the construct of "mental states" (such states as belief and fear and desire) do not exist and cannot be used to explain cognitive functions or phenomena. Keywords: Cognitive Science anxiety References: Stich, 1996
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emotion

A conscious phenomena of responsiveness. We respond to circumstances and to specific inputs with combinations of mental and physiological reactions. The mental reactions are part of cognition. The physiological responses vary but involve the respiratory, cardiovascular, and other body systems. These are often chemically induced and mediated by the limbic system (hypothalamus and amygdala). Keywords: subjective response objective hypothalamus thalamus cognition amygdala limbic system References: cognition comprehension fuzzy logic inference knowledge logic
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empiricism

Empiricism is a system of learning and discovery that relies heavily on observation without formal scientific methods such as experimentation. Empirical knowledge is often that gained in the course of living and communicating with others without necessarily being mathematically or scientifically verifiable. Keywords: theory behavior experiment uncertainty References: chaos formalisms learning philosophy
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endocytosis

Recovery of neurotransmitter for reuse by the cell. Without this process, chemical imbalances would build up in the brain and/or cognitive abilities would be dulled by the increased time required to synthesize the chemical resources necessary for E/I transmission between neurons. Keywords: exocytosis E/I action potential synapse References: brain physiology neurons neuroscience
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English

A human communication system based on exceptions rather than rules. According to Winston Churchill, a recognized user of English, its main strongholds, the United States and Great Britain, are "two great nations separated by a common language." Keywords: grammar language natural language References: lexicography linguistic strata natural language semantics syntax words/morphology
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Enterprise Knowledge Management (EKM)

Knowledge HierarchyDepending on the maturity of the organization, EKM can mean anything from organizing educational content (packaged learning materials), to enabling the semantic enterprise with machine learning, natural language search and query, converged metadata management and knowledge curation and governance processes and tools. In the basic case, a catalog and managing sources of record and publishing processes are enough to bring significant business value. In advanced cases, at the end of major investment, organizations develop competitive advantage with rapid insights into changes in consumer behaviors and market pressures.
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entropy

The useful information content of a message evaluated in terms of uncertainty. Keywords: comprehension noise meta-knowledge forget certainty information uncertainty References: comprehension context information/entropy intelligence learning
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environment

Computer Program FlowAn ecosystem of capabilities a software engineer uses to weave magic digital fabric. TutorialsPoint says: Though Environment Setup is not an element of any Programming Language, it is the first thing we need to start programming with any Programming Language. you will need following setup to start with programming using any programming language.
  • A text editor to create computer program.
  • A compiler to compile program into binary format.
  • An interpreter to execute program directly.
(TutorialsPoint) There's more. See my post on choosing an Environment.
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episodic knowledge

Memory of events that have already happened. Episodic memory can be used for inference and for learning procedural and declarative knowledge. A past event in episodic memory is an experience. Once the sensory elements are stripped and the event becomes history, it becomes declarative. Keywords: experience procedural knowledge declarative knowledge knowledge declarative memory procedural memory intelligence References: associationism cognition inference knowledge taxonomy
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epistemology

The study of the origin and character of knowledge. Epistomological research attempts to answer questions about methods of acquiring, storing, accessing and using knowledge, about the bounds or limits of human knowledge capacity, and about the general nature of knowledge. Keywords: knowledge acquisition memory learning References: associationism cognition inference knowledge taxonomy
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equation

Mathematical formulae or equations are a symbolic form of propositional logic. We must accept the values of the symbols (numbers and variables) and the functions of the operators for the propositions to be well-formed. A formula probably must be well-formed to be correct but while improper structure implies incorrectness, proper structure does not imply correctness. Keywords: combinatorial explosion range quantifiers proposition logic rule fact reasoning form formalism References: algorithms automata computing logic rules
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ERP - Event Related Potential

  1. Evoked Response Potential: Electric flow in the brain resulting from some external stimuli
  2. Event Related Potential: Electric flow in the brain resulting from some external stimuli
  3. Enterprise Resource Planning: An amalgam of processes often associated with financial accounting, supply, demand, manufacturing, selling and/or fulfilling in commerce.
WebMD describes tests for ERP: Posts: Brain Signal Variations An evoked potential test measures the time it takes for nerves to respond to stimulation. The size of the response is also measured. Nerves from different areas of the body may be tested. Types of responses are:
  • Visual evoked response or potential (VER or VEP), which is when the eyes are stimulated by looking at a test pattern.
  • Auditory brain stem evoked response or potential (ABER or ABEP), which is when hearing is stimulated by listening to a test tone.
  • Somatosensory evoked response or potential (SSER or SSEP), which is when the nerves of the arms and legs are stimulated by an electrical pulse.
Event Related Potentials
Keywords References
action potential  The Curve
impulse
E/I

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exception

A deviation from a rule. Exception may be a misnomer. Whenever you find an exception, you are likely to find the action of a different rule that brought about the exception. To accept the idea of an exception, we must first agree that all rules are absolutely true or false. In multi-valued logic, we attempt to find the rules that are being followed and ignore those that are not. Multi-valued logic presupposes that there may be no such thing as an exception. Keywords: standard deviation inference rule fact logic proposition determinism multi-valued logic fuzzy logic References: automata information/entropy rules
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existential

Applicable to that which exists. Existential meditation seeks to find deeper meanings in life through introspection and deep thinking. Existential knowledge is simply knowledge of things that exist (described in object-oriented programming as objects). It includes descriptive knowledge of the properties of things. Keywords: causal relation descriptive relation knowledge representation object object-oriented abstraction thought property References: associationism cognition inference knowledge taxonomy
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exocytosis

Secretion of neurotransmitter chemical to facilitate the propagation of E/I. The chemical secretion begins a chain reaction that results in exchange of electrical potential from the axon of the sending cell to the dendrite (or other part) of the receiving cell. Keywords: E/I endocytosis action potential spike References: brain physiology neurons neuroscience
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expectations

When we anticipate what is likely to happen in the near future, we become cognitively prepared for it to happen. By building expectations, we make recognition and comprehension more efficient by warming up those areas of our brains that will be needed. Keywords: extra-sensory recognition learning think sense anxiety prediction References: context knowledge representation logic perception taxonomy
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experience

As we go through life and remember the episodes of success and failure, we gain a repertoire of knowledge about how things work. This knowledge is often called experience. Keywords: episodic knowledge causal relations memory meaningful association relation References: cognition comprehension context fuzzy logic inference knowledge logic perception
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experiment

In the scientific method, researchers like to prove theories to be true by showing that experimental results bear out hypothetical predictions. Experimental observation is typically much more rigorous and methodical than empirical observation. Keywords: empiricism uncertainty References: inference learning philosophy
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expert system

An artificial intelligence (AI) based system that performs some task that normally requires a certain level of human expertise. Expert system machines usually perform inferences using a set of rules to interpret input and generate intelligent-sounding output. Keywords: production system rule fact domain blackboard AI inference rule base knowledge base decision support system References: AI programming algorithms automata computing formalisms logic rules
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explicit representation

A knowledge representation scheme where the knowledge is stored as symbolic logic or some other form that is readable by humans. Compare with implicit representations where the knowledge is stored as a set of states and weights that are not readable by humans. Keywords: relation descriptive relation References: algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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exposure

Adaptation in biological systems requires some external influence over some period of time. The combination of influence and time can be described as exposure. The influence of light on the emulsion of camera film exposes the film. The influence of input stimuli on the brain exposes the neural network. The duration and intensity of exposure determines the speed and extent of adaptation. Keywords: adaptation learning genetics genetic algorithms input References: cognition comprehension inference knowledge learning perception
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expression

A form of speech, particularly colloquial, used to represent a concept or object. To express means to put something that exists into a linguistic symbol that is intended to convey what is in the speaker's (or writer's) mind to the hearer's (or reader's) minds. The indignant expression "It's just an expression" is usually used in an argument to deflect the attention of the hearer away from the fact that the hearer properly interpreted the speaker's malignant intent. Keywords: expressiveness laughter response reflex communication language natural language translation association learning perception References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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expressiveness

Expressiveness is a measure of the degree to which artwork or language or a performance reaches the intended audience. In art, expressiveness does not always reflect a meeting of minds in that audiences can interpret the expressive art in any way. In language, however, success in conveying and interpreting the same thing is critical. Humor is an expressive form of language art in which the interpreter is often asked to discern multiple meanings in a single utterance. Keywords: idiom sememe semantics noise meaningful interpretation expression communication language natural language translation association learning perception References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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extra-sensory

Perception or perceptiveness that cannot be credited to sight, hearing, taste, smell or tactile input: a sixth sense. Usually, extra-sensory perception involves high levels of sensitivity to context and the ability to correlate much episodic and ascriptive knowledge to build expectations that would not be possible without the integration of significant amounts of knowledge. Extra-sensory perception may be considered a higher-than-ordinary level of consciousness or sensitivity. Keywords: sensory perception sense knowledge context expectations integration References: associationism cognition inference knowledge taxonomy
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fact

A thing that is. The truer the fact, the better. False facts tend to be confusing. In expert systems facts are items of information fed into the system for processing. The facts are compared with rules in the system to find patterns and inferrable results that can lead to conclusions. Keywords: proposition interaction equation rule rule base exception expert system inference domain input behavior References: algorithms automata computing knowledge logic rules syntax
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feature

A feature, in the context of perception, is a basic component of an image, sound or other perceptible object. Features of sounds include their pitch, volume, duration, and decay. Features of images include the orientation of each of the lines and contours, light intensity, color, hue, direction of motion, and speed. In information processing, finding features of things such as images, sounds, words and sentences is essential for correct recognition and interpretation. These features become constraints. Keywords: perception property constraint image processing References: learning memory neurons semantics
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feedback

In physiology, signals sent to the brain from monitored organs and senses. In psychology, signals or cues that help us confirm our interpretation of input. In neural nets, back propagation of error signals to assist in correcting or adjusting weights in the learning process. Keywords: neural network Martinotti granule cells Golgi cells References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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filtering

In a perceptual environment where we are flooded with visual, audio, tactile and other stimuli, we must focus on some things and ignore others. The process of ignoring others is filtering while focusing is called attention. Without a filtering mechanism, we would be the victims of cognitive overload. Keywords: RAS attention context perception sense ART learning References: chaos inference logic probability
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firing

The process of a nerve cell or a neural network node becoming activated. When electrical potential is applied to neurons or nodes in an artificial network, until the potential reaches a certain threshold the cell is said to fire, permitting it to further propagate electric potential. Keywords: neural network decay anticholinesterase activation neuron E/I threshold action potential spike References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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flip-flop

flip-flop

Flip Flop 1) A politician changing his position 2) A single register in memory or a processor of a circuit, particularly an integrated circuit, is called a flip-flop. Transistors and gates are used to store a charge that represents 1 or 0 in digital logic. 3) Either a left or a right beach style sandal (ie. the singular of flip-flops)
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forget

Erase human memory of a thing, event or association. The delete key on a computer is used to help computers forget. The things that cause or motivate humans to forget are much more complex. Keywords: memory recall data information learning entropy References: learning memory pathology
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form

The first half of the dichotomy "FORM and FUNCTION." Form consists of the describable structure of a thing (i.e. what it looks, sounds, feels, smells, or tastes like, or how it is assembled). Form does not deal with what it does – that is the responsibility of FUNCTION. Keywords: symmetry taxonomy syntax formalism equation arity function pattern structure References: algorithms automata computing formalisms logic rules syntax
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formalism

A well-defined set of assumptions, structures, functions, or all of the above that are used to accomplish an end such as manage a project or design and build a better mousetrap. Keywords: quantifiers distributed methodology form function equation References: algorithms automata computing formalisms logic rules syntax
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fractal

Designs created by computers based on mathematical formulae. The formulae typically use a combination of self-similarity and quasi-random elements to draw interesting designs whose individual components, lines, shapes and/or colors are duplicates or mirror-images of one another. Keywords: self-similarity imagination creativity random References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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frame

A knowledge representation scheme using a table with labeled slots, each of which accept fillers that match the category of the slot. Filling and processing frames can be constrained by any active heuristics or symbolic logic rules. Keywords: semantic network conceptual graph knowledge representation heuristic inference AI References: AI programming algorithms automata computing formalisms logic rules
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frenetic

Frantic or frenzied. In the original Greek, it meant "mad or suffering from the common ailment of inflammation of the brain" – we're talking wacky. This is the word that most commonly comes to mind as I consider my deadlines for getting NeuroPedia to press. Also spelled phrenetic. Keywords: phrenology introspection personality References: brain physiology neurons neuroscience learning pathology psychology
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function

How things work or how they do what they do. Combining a knowledge of function and form (or structure) is necessary for complete analysis of a thing and for designing simulations such as those attempted in cybernetic research. Imitating the functions of human thought, for example, is a primary goal of AI. Keywords: modularity interaction formalism decision data-driven data type code behavior arity argument form structure pattern process References: AI programming algorithms automata computing formalisms logic rules
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fusiform cells

fusiform cells

A type of neuron found in the cerebrum, characterized by different shapes (sorry for the vague definition – why don't you read about it in one of the pages here?). Modeling Neural Interconnections Varieties of Nerve Cells Fusiform Cell Morphology
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fuzzy

Reasoning techniques that apply to constraints, multiple values of truth, or confidence to solve problems. Fuzzy techniques can be used in computer algorithms that mimic human cognition to overcome the brittleness of programs that can only address two possible values (true or false) in judging issues. Recognizing shades of truth or confidence enables AI programs to suggest possible answers when none is certain. Keywords: multi-valued logic confidence belief chaos non-determinism logic dichotomous logic fuzzy logic AI References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition
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fuzzy logic

Fuzzy Guy A form of reasoning that incorporates multiple criteria for making decisions and multiple values for evaluating possibilities. Fuzzy logic differs from dichotomous logic in that, while dichotomous logic expects to derive a solution by deciding whether each of the constraints or parameters is true or false, fuzzy reasoning permits scales of conditions and shades of values. It is less interested in truth and more in practicality. Fuzzy Logic and the Mind-Brain Dichotomy Context Powers Backward Chaining Logic Dichotomy vs. Continuum
Keywords References
paradox  algorithms
exception  associationism
chaos  chaos
constraint  connectionism
confidence  fuzzy logic
logic   belief  neural networks
multi-valued logic  learning
determinism   non-determinism
dichotomous logic
fuzzy     AI  pattern recognition

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gamification

Mary Poppins suggested that in every job that must be done, there is an element of fun - you find the fun and snap, the job's a game. That advice and a spoonful of sugar might not buy you a cup of coffee, but I'm game to try it out. My definition for gamification of software is to add challenges, levels and rewards to any automated task and you're well on your way to making it fun.
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Gamma Oscillations

From Nature: http://www.nature.com/nrn/journal/v8/n1/abs/nrn2044.html Gamma frequency oscillations are thought to provide a temporal structure for information processing in the brain. They contribute to cognitive functions, such as memory formation and sensory processing, and are disturbed in some psychiatric disorders. Fast-spiking, parvalbumin-expressing, soma-inhibiting interneurons have a key role in the generation of these oscillations. Experimental analysis in the hippocampus and the neocortex reveals that synapses among these interneurons are highly specialized. Computational analysis further suggests that synaptic specialization turns interneuron networks into robust gamma frequency oscillators.
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generalization

A process of conceptually linking words, things or objects to other words, things or objects that have some shared characteristics. Children generalize about linguistic form throughout language acquisition, sometimes correctly inferring transformations to words that change their tense or number. Parents usually notice generalization when the children fail to corrently change a word to change its tense or number, such as the word "goed" for "went". Keywords: theory taxonomy creativity categorize References: cognition comprehension context fuzzy logic inference knowledge logic perception
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genetic algorithms

"Search algorithms based on the mechanics of natural selection and natural genetics. They combine survival of the fittest among string structures with a structured yet randomized information exchange to form a search algorithm with some of the innovative flair of human search" [Goldberg, 1989]. Keywords: survival heredity genetics exposure adaptation DNA search References: Goldberg, 1989 Holland, 1975 algorithms genetics computing
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genetics

The study of human heredity. Genes bear information in helical structures called DNA. This information determines the physiology of the species by enforcing its code on the offspring. Good code is likely to produce a survivable organism while poorer code may leave one out of luck. Keywords: survival RNA exposure adaptation DNA heredity ALife genetic algorithms References: Goldberg, 1989 Holland, 1975 genetics
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GIGO

Garbage In, Garbage Out. This is the arrogance and frailty of early programmers. If the input was not exactly what the computer expected, then it was garbage, and the only possible output would be garbage. For the first several decades of computing, this paradigm stood, much to the consternation of most users. We are beginning to turn a corner in which the computer will attempt to deliver good output even with imperfect input.
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gnostic

From the greek gnostikos [knowing] – sagacious, quick to recognize. Able to interpret form or combine elements to perceive the whole. In neurocognitive theory, gnostic cells are neurons that are capable of "knowing" about something or possessing memory of something complex (such as the image of Grandma's face). Keywords: memory learning neuron cognition References: associationism cognition inference knowledge
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Golgi cells

A cell type found in the granular layer cerebellum that has extensive dendrite arborization in the molecular layer and many axon processes in the granular layer. The axon synapses provide feedback to granule cells. Keywords: cerebellum granule cells stellate cells purkinje mossy fibers feedback References: brain physiology neurons neuroscience
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governance

A discipline of controlling chaos with established processes and standards. In IT there are often Portfolio and Data Governance initiatives to simplify and reduce duplication across systems. From the Business Dictionary: Establishment of policies, and continuous monitoring of their proper implementation, by the members of the governing body of an organization. It includes the mechanisms required to balance the powers of the members (with the associated accountability), and their primary duty of enhancing the prosperity and viability of the organization. See also corporate governance.
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graceful degradation

A characteristic of a computational system that does not break when it does not like what you tell it. In other words, a system that may put out something other than garbage when the input would be treated as garbage by more rigid or inflexible systems. In natural language processing systems, graceful degradation is a must because not all people use absolutely perfect language all the time. In fact, few people use perfect language ever. References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference modeling system engineering
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grammar

A formula or set of formulae used to describe logical relationships between lexical items or other terminal symbols. Grammars are used in language, math and logic to describe (or prescribe) the structure of a human or artificial language. Keywords: ATN word syntax strata sentence recursive language English dichotomous logic determinism context-free context-sensitive regular References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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granularity

This word is important in parallel computing and problem decomposition. When we solve a problem using a divide-and-conquer approach, granularity is the word we use to describe the coarseness or fineness of the pieces after we have divided the problem. The pieces of a computational problem computed on different processors of a parallel machine possess a granularity describing the coarseness or fineness of pieces of code that go to each processor. This is where modularity comes in: the finer the granularity of code modules, the closer we can approach a "knowledge driven" technical ecosystem. Keywords: SIMD MIMD parallel computing decomposition References: algorithms automata computing formalisms logic rules
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granule cells

A small cell type found in many areas of the brain that, like cells of Martinotti, sends axons up to the surface instead of down to the white matter. This lets them propagate new impulses and feedback toward the cortex surface. A cerebellum layer is called the granular layer due to the profusion of granule cells there. Keywords: Martinotti feedback cerebellum mossy fibers stellate cells Golgi cells Purkinje References: brain physiology neurons neuroscience
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gray matter

The cortex parts of the brain are gray in color because of the profusion of neurons and their dendrites with grayish membranes. White matter is white because of myelin. The word cortex is often used synonymously with the cerebrum, but, in fact, the cerebellum has cortex also. Keywords: cortex dendrite white matter gyrus sulcus References: brain physiology neurons neuroscience
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GUI

Graphical User Interface. Computers and humans, when they need to interact, need an interface. The easier for humans to learn and use the interface, the better the interface is presumed to be. The folks at Xerox Palo-Alto Research Center (PARC) designed the first graphical (windowed) interface that was later used by Apple in their Macintosh line and yet later by Microsoft in their Windows lines of products. Keywords: computer computing automata modeling comprehension References: algorithms automata computing
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gyrus

Gyri are ridges in the cortex. They give the brain its interesting topography. They are divided from each other by the sulci. The gyri are both physically and logically separated folds in that they serve distinct functions. Keywords: cortex sulcus gray matter References: brain physiology neurons neuroscience
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Hadoop

Volume Velocity and VarietyHadoop refers to an open source big data system and software library is a framework that supports distributed processing for large data sets using clusters of computers and simple programming models. It can be deployed on a single server, or up to thousands of machines, distributing both computation and storage capabilities needed to handle the increasing volume, velocity and variety of information in today's interconnected world. http://hadoop.apache.org/
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heredity

The phenomenon of transmission of biological or other personal characteristics from parent to child. Heredity is mediated by the storage and transmission of information stored in DNA. Keywords: innate DNA genetics genetic algorithms References: Goldberg, 1989 Holland, 1975 algorithms genetics computing
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heuristic

According to ANSI/IEEE Std 100-1984, heuristics are exploratory methods (algorithms) for problem solving in which solutions are discovered by evaluation of the progress made toward the final result. Keywords: schemata problem frame argument algorithm stochastic References: ANSI/IEEE, 1984 algorithms automata computing expert systems inference rules
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hierarchical relation

A taxonomical way to classify things that are related to one another in such a way that when you go down one level, the objects inherit the characteristics of the higher level. The family structure is hierarchical as is the biological classification tree with kingdoms, phyla, genus, species, etc. Keywords: taxonomy relation descriptive relation categorize causal relation knowledge References: associationism cognition inference knowledge taxonomy
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hippocampus

The part of the brain that may be responsible for telling us where we are. If you open your eyes and say "Where am I?" you may have a case of HIPPOCAMPUS CRAMPUS, though it could just be a case of residual adolescence. Keywords: central nervous system limbic system context amygdala hypothalamus thalamus References: brain physiology neurons neuroscience
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horizontal cells

Also called cells of Cajal, horizontal cells are found in the outermost layer of the cerebrum. They extend their receptive dendrite fibers laterally along the surface of the gray matter. Their primary function is correlation, or providing linkages for cells distant from each other. Keywords: basket cells cerebrum correlation Martinotti pyramidal cells References: brain physiology neurons neuroscience
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hybrid IT

An information technology section or division in an organization that is composed of both internal and external vendor personnel, systems and capabilities. The capabilities, in particular, include maintenance and support, which becomes more complex as more capabilities are sourced to the "cloud" as managed services, hosting, Software as a Service, Infrastructure as a Service, Platform as a Service, or even, IT as a Service.
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hypermnesia

Remembering more than before. This is the opposite of amnesia, which is forgetting. The concept is based on the fact that we take in a lot, our brains retain a bunch of what we take in, we only have conscious memory of part of what our brains retain, and by doing associative exercises we can sometimes access more of what our brains retained than we could before the exercises. Keywords: amnesia memory learning association References: cognition knowledge memory
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hyperpolarization

Inhibition of electric potential in a neuron or artificial model so that the electric potential of the cell falls below resting potential. This is the opposite of excitation, and it effectively reduces the flow of positive electric potential. Keywords: overshoot activation action potential depolarization E/I threshold References: brain physiology neurons neuroscience
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hypertext

A method of linking words or other screen objects in a computer application or environment. The link typically connects a word to other information related to the word. This model was popularized by the Hypercard application available on the Apple Macintosh, then later migrated to other computing platforms and to the World Wide Web on the Internet. The World Wide Web uses HTML, which stands for HyperText Markup Language. Keywords: architecture cue distributed interaction non-determinism paradigm search References: algorithms computing formalisms logic
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hypothalamus

A part of the diencephalon that maintains proper levels of body fluids, heart rate, and other functions critical to survival. The things regulated by the hypothalamus are subject to disruption by emotional responses to certain stimuli, so the hypothalamus can help us stabilize when we're under duress. Keywords: hippocampus diencephalon thalamus emotion amygdala limbic system References: brain physiology neurons neuroscience
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iatric

Medical or having to do with medicine or medical doctors. Derived from the Greek iatrikos or iatros (physician) or iasthai (to cure). This word is only in the glossary to help you solve the crossword puzzle. Keywords: neuroanatomy References: brain physiology neurons neuroscience
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idiom

A colloquial expression that often either simplifies the language necessary to convey a meaning or adds salient denotations or connotations to a phrase. Poetry often builds idiomatic language by combining words and concepts in ways that can elicit multiple interpretations or emotional responses. Idiomatic language is often the most expressive and the least grammatically correct. The extent to which language- or culture-specific idioms appear in text determines the difficulty of translation. Keywords: word sentence understanding meaningful expressiveness translation References: chaos comprehension fuzzy logic natural language words/morphology
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image processing

When we see things, or when computers receive video input, it must be processed in order to be interpreted. Processing may involve feature extraction and synthesis. Keywords: perception feature computing algorithm sensory References: algorithms comprehension computing neural networks pattern recognition perception vision
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imagination

A cognitive process of conjuring images or abstract ideas of how things could be in an imaginary world, whether or not they could possibly be so in the real world. Many cognitive scientists speculate that imagination is unique to humans, though this may be difficult to prove. Keywords: self-similarity fractal cognition concept creativity psyche References: cognition comprehension context fuzzy logic inference knowledge logic perception
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impedance mismatch

ERD - Entity Relationship DiagramObject-oriented programming languages enable developers to build systems, services and applications out of objects that have both data and behavior (methods).   Relational databases store data in tables bound together through primary and foreign keys. Object-oriented programming is based on time-tested software engineering principles while the "relational" paradigm is based on mathematical principles.  Because the underlying paradigms are different the two technologies require an intervening transformation layer to work together seamlessly. "The impedance mismatch becomes apparent when you look at the preferred approach to access: With the object paradigm you traverse objects via their relationships whereas with the relational paradigm you join the data rows of tables. This fundamental difference results in a non-ideal combination of object and relational technologies" (Scott Wambler at Agile Data).
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implicit representation

In a distributed processing scheme such as a neural network using adaptive learning techniques, many processing or memory elements can be trained to recognize inputs without ever storing a copy of the input in memory. Keywords: knowledge representation knowledge representation cognition memory References: associationism cognition inference knowledge logic taxonomy
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impossible

Any event or occurrence which cannot occur. In threshold logic, the possibility of any event would fall either above (possible) or below the threshold (impossible). Nothing could straddle the line. Threshold logic applied to possibility is context-governed; consequently, some events may be possible in some contexts and impossible in others. If nothing is impossible, this does not apply. Keywords: possible probability References: chaos inference logic probability
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impulse

1) Shoppers buy things they do not need on impulse, a kind of irrational attraction. 2) The auxiliary power system in a star ship produces impulse power. 3) In Neuroscience impulse normally refers to an electrical charge of action potential that flows in the brain. Impulses can be positive (excitatory) or negative (inhibitory). Keywords: quantal release software E/I action potential input thought References: brain physiology neurons neuroscience
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inductive reasoning

Electronic ThoughtsInductive reasoning is a bottom-up or forward-chaining model that makes broad generalizations about knowledge based on specific facts or observations. In a step-by-step process or computer program, inductive reasoning techniques may look at the facts or variable values you have accumulated so far, then branch based on a rule that applies to those variables. Livescience on Deductive vs. Inductive reasoning
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inference

The logical process of navigating from the known to the unknown. When rules of traditional (Aristotelian) or multivalued (fuzzy) logic are followed, it is often possible to act as a detective to piece together the clues and arrive at a solution. Some people are very good at it. AI trys to teach it to computers. Keywords: production system symbolic logic statistical analysis rule base rule reasoning reason modus tollens modus ponens learning knowledge base knowledge interaction frame fact expert system domain declarative knowledge decision support system constraint interpretation logic proposition exception cognition AI References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation
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information

Correlated pieces of data that are generated, stored, analyzed, interpreted or transmitted. A single datum or unrelated data items are generally not information. To be information, there must be a link between data items. Keywords: zygote uncertainty space software representation RAM noise NeuroPedia knowledge representation forget conceptual graph certainty entropy data References: associationism cognition inference knowledge taxonomy
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inheritance

What the prodigal enjoyed squandering. Also, a technique used in object-oriented design and development that permits objects of a descendant or sub-class to acquire characteristics of a parent or super-class. Keywords: taxonomy polymorphism object descriptive relations class categorize object-oriented composition decomposition abstraction References: Goldberg, 1989 Holland, 1975 algorithms genetics computing
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innate

Inherited or present at birth. Innate abilities are part of the legacy with which humans are born. Some survival instincts are innate, as are the underlying cognitive abilities to recognize, generalize and reason. There is some argument as to whether or not certain language capabilities are innate. These issues are discussed in Volume 6. Keywords: heredity cognition learning References: associationism cognition genetics inference knowledge taxonomy
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input

1) The process of putting data and/or programs into a computer's memory or processor for processing. 2) The information that is put into a computer, etc. 3) Any data, knowledge or opinion that is provided to someone or something to assist in the decision-making process. Keywords: rule parsing output olfactory impulse fact efferent data processing data cue code perception exposure mechanical brain sense afferent References: algorithms automata computing
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instinctive

Actions or responses that seem to be innate or so ingrained in a person's psyche that they are automatic. Reflex actions are called "knee-jerk reactions." There are physiological things such as elevated heart rate and hypersensitive skin (goose bumps) that are built into the nervous system. These are even more instinctive than reflexes. Keywords: learning reflex response References: Goldberg, 1989 Holland, 1975 genetics
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integration

In cognition, the input of multiple senses is often integrated to analyze the input of one sense. For example, what we see may help us interpret what we hear. Previously acquired knowledge is integrated in the interpretation process, though this is often refered to as "association." Keywords: extra-sensory diencephalon tactile agnosia spinal cord reflex association sense interpretation thalamus correlation cue References: cognition learning pattern recognition
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intelligence

The ability to reason, deduce, infer, guess, and apologize for being wrong. Keywords: think sense reason procedural knowledge perception organism cue thought cognition brain knowledge declarative knowledge episodic knowledge References: associationism cognition inference knowledge taxonomy
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interaction

In the functional universe, things act and interact. The interaction of things in their domains form the basis for rules and propositions. In multi-dimensional models such as 3-D Grammar, in which there are several strata that are like independent domains, the interactions of facts and rules across adjacent domains are the most computationally interesting characteristics. Keywords: hypertext causal relations function domain context object rule inference fact References: cognition comprehension context fuzzy logic inference knowledge logic perception
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intermediate filaments

IF: The medium-sized cytoskeletal components that provide the structure for cell components such as nerve fibers and cilia. Cytoskeleton
Intermediate filaments are broadly discussed in Cytoskeleton Components in Cognition    Axon and Dendrite Growth
Keywords References
cytoskeleton  brain physiology
microtubules  neurons
axoplasm  neuroscience
 
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interpretation

Whenever we get sensory input such as seeing or hearing something, our brains interpret it. "Interpret" is often used in the context of language, but it can apply to sensory or abstract input including feedback from our own bodies (i.e. interpret our emotions). Keywords: comprehension discern strata segmentation recognition parsing MT logic integration inference declarative knowledge cue context acquisition communication language natural language translation association learning perception expressiveness References: cognition comprehension context fuzzy logic inference knowledge logic perception
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introspection

Self-awareness, analysis or discovery. After the ME decade (1970s USA), a resurgence of less selfish introspection has lead to a kinder, gentler way of perceiving one's self and one's position in the universe. Self is a critical component of context, thus cognition depends on introspection. Computers can only do it for medical purposes... Keywords: personality frenetic phrenology References: cognition comprehension fuzzy logic inference knowledge logic
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intuition

An advanced cognitive capability consisting of common sense, prescience, and an understanding of human nature. Intuitive thinkers are often able to respond to complex situations more quickly or more appropriately than overly logical thinkers. Intuition in western cultures is often stronger among females than males. There have been scientific studies linking certain hormones with intuition. Intuition strengthens in familiar contexts and weakens in unfamiliar contexts. Keywords: thought cognition decision context References: cognition comprehension context fuzzy logic inference knowledge logic perception
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involuntary

Physical functions that just happen whether we want them to or not. Metabolic (digestion), respiratory (breathing) and cardiopulmonary (heartbeat and blood flow) activities are involuntary in living organisms. Many reflex actions are also involuntary. Keywords: autonomic nervous system References: brain physiology neurons neuroscience
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ion pump

Mechanisms in the membrane of neurons that exchange chemical ions between the cytoplasm inside cells and the fluids outside cells. This exchange is necessary to maintain equilibrium and restore the proper electrical potentials after electrical activity has disrupted the resting potential of a neuron. Keywords: neuron dendrite axon References: brain physiology neurons neuroscience
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judgement

  1. Enforce the RulesA day when we all stand before the bar of God
  2. A "rational" decision based on evidence
    • in a court of law
    • in the course of deciding how to act, where to go, and how to respond to any possible situation
Isn't it really spelled judgment?
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kd (kilodalton)

A dalton is a unit of mass 1/16 of an oxygen atom or roughly  1.65 X 10 -24 grams.
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kinesthesia

Perception of internal stimuli that enable us to self-monitor our feelings, well-being, and the position of our limbs in relation to our body position. Keywords: stimulus response reflex sense References: cognition context perception
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knowledge

Could it be something we have in our brain that we can remember later? For instance, we learn that c follows b's preceded by a. Then we associate these letters with sounds and words and use words to describe our world. In data theory, knowledge is compound data that is independently meaningful. Keywords: extra-sensory understanding theory strata short-term memory schemata rule base recall procedural memory meta-knowledge mamillary bodies knowledge representation implicit representation hierarchical relations episodic memory discriminate discern declarative memory common sense causal relations epistemology intelligence learning memory proposition declarative knowledge episodic knowledge procedural knowledge logic inference comprehension References: associationism cognition inference knowledge learning memory taxonomy
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knowledge base

A database with more. Rather than a collection of records set up with various fields, a knowledge base (KB) has information that is intrinsically expressive of the way things are in the real world. The distinction blurs in several areas, but a KB is generally supposed to be smart. Keywords: model base decision support system rule base inference expert system References: associationism cognition inference knowledge learning memory taxonomy
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knowledge representation

In artificial intelligence, some consistent and useful way of organizing information in the computer is necessary to facilitate processing. This is called the knowledge representation (KR). Common KR schemes include symbolic logic rules, frames, semantic networks, and conceptual graphs. Keywords: existential symbolic logic schemata frame semantic network information knowledge representation conceptual graph implicit representation References: context knowledge representation logic taxonomy
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knowledge worker

A knowledge worker is a person or intelligent device that is or was employed during or after the information age (you and me both).
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language

A set or system of symbols used to communicate. Languages are usually governed by rules (always syntactic and semantic) that constrain exactly how we arrange the symbols to communicate the desired message. The expressiveness of the language increases exponentially with the size of the lexicon. The complexity of interpreting a language increases with the number of rules that can be applied. Keywords: symbol strata sentence semantics segmentation pragmatics morphology linguistics lexical expressiveness expression creativity anaphora acquisition natural language communication interpretation translation grammar English cognition References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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laughter

A universal form of personal expression often associated with group activity. Daniel Dennett describes the phenomenon as "involuntary, convulsive respiration, a sort of loud, helpless, mutually reinforcing group panting that sometimes is so severe as to incapacitate them" (Dennett, 1991, p.62). Keywords: expression response reflex References: brain physiology neurons neuroscience learning pathology psychology
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laughter

Laughing Woman Another universal human response that becomes a form of communication, laughter is like crying, rolling eyes and running in the opposite direction. It's the best medicine - and it is a conscious phenomenon.
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learning

A process of gaining new knowledge of objects, phenomena or procedures, or new knowledge of relations between objects and/or phenomena. It can be primitive enough for a machine to do (such as a robot learning to pick up a bolt) or so complex that even humans often fail to achieve it. Keywords: specialization segmentation prediction logic linguistics knowledge instinctive innate hypermnesia gnostic forget filtering expressiveness expression exposure expectations epistemology descriptive relations cue creativity common sense amnesia adaptation perception interpretation proposition AI ALife ART inference cybernetics References: associationism cognition inference knowledge learning memory taxonomy
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lexical

Having to do with known words. A lexicon is the list of words known to a language, person, or system. Keywords: sememe word language linguistics ambiguity morphology References: comprehension natural language words/morphology
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lexicon

The words (and idiomatic phrases) used in a language or by a person, group of people or a computational system. I add idiomatic phrases to the lexicon because the intent of the idiom is often completely different from the sum of its parts. noun \ˈlek-sə-ˌkän also -kən\   Lexicon Valley from Slate
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limbic system

A brain system managing physiological responses to emotions. The limbic system is associated with behavior. It includes the thalamus, hypothalamus, amygdala, and parts of the reticular formation, brainstem and cerebral cortex. Keywords: hippocampus emotion amygdala hypothalamus thalamus References: brain physiology neurons neuroscience
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linear discrimination

A process of classification or recognition used in neural network processing. By passing input into a trained linear feed-forward network, both discrimination and learning processes of the human brain can be simulated. The success of linear discrimination as a processing mechanism has fed the connectionist movement and lead to the development many robust models of human cognition. Keywords: neural network categorize recognition link neurode connectionism References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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linguistics

The study of natural language and languages. Computer languages are regular in that they are strictly obedient to a finite set of rules. Human languages are, by contrast, rebellious and dynamic. They change daily, and as they change they accumulate rules. Computer languages that violate syntax rules don't work. Human language works though it seldom strictly obeys rules. Keywords: sememe semantics pragmatics lexical cognition language communication rule learning syntax morphology References: chaos comprehension fuzzy logic lexicography linguistic strata natural language words/morphology
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link

A link connects one thing to another. Physical links in the brain (synapses) are probably the most operative element in cognition. Links between concepts enable us to do complex reasoning and make inferences. Links between words in text or speech give us the cues we need to interpret language. Links between processors in parallel computers can be used to simulate some of these kinds of links. Keywords: relation neurode linear discrimination descriptive relations association synapse node ANS neural network semantic network References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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local potential

A less common type of change in the electrical potential (voltage) of a neuron either caused by receptor stimuli (such as neurons that respond to tactile sensations of texture, temperature and pressure) or postsynaptic potentials that arise from electrical activity emanating from other cells/fibers rather than from a connected synapse. Keywords: action potential E/I neurotransmitter stimulus response References: brain physiology neurons neuroscience
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logic

Derived from the Greek logos (reason – the governing principle in the universe): a set of rules used to make credible inferences. Aristotle recommended dichotomous, true-false logic. Oriental philosophers tend to use multi-valued or fuzzy logic. Both techniques are useful in modeling human cognitive processes on computers. Keywords: production system subjective reason quantifiers prediction paradox non-determinism multi-valued logic modus tollens modus ponens logorrhea knowledge fuzzy logic fuzzy exception equation dichotomous logic determinism declarative knowledge constraint inference objective learning logical form interpretation cognition proposition References: cognition comprehension fuzzy logic inference knowledge
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logical form

A language-based way of representing real-world phenomena. Syllogism is a classical structure in logical form in which the premises are stated (i.e. IF a AND b) and the conclusion drawn (i.e. THEN c). The mathematical integrity of logical form makes it attractive for computing. Keywords: OOPS modus tollens modus ponens logic syllogism causal relations References: cognition comprehension formalisms fuzzy logic inference knowledge logic
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logorrhea

Diarrhea of reason; incoherent and/or excessive verbosity or a tendency to ramble on. The author of this blog has often been diagnosed with this all too common malady. A recipe for curing it involves an apple in the snout and an oven preheated to an appropriately high temperature to humble the victim of this affliction. Keywords: logic reasoning References: cognition comprehension fuzzy logic inference knowledge logic
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machine learning

Digital Graph BrainA branch of cognitive computing or artificial intelligence (AI) that gives computers the ability to learn new facts, associations, and possibly processes automatically. This implies that humans may code the rules, and tell the machine where to look, but the ML takes place without real-time human participation. With supervised learning, any inferred facts, associations or processes will later be reviewed by a person to validate correctness or assign confidence values. The process-centered branch of ML focuses on developing computer systems that can teach themselves to grow or change based on new data.The content-centered branch of ML uses new facts and associations to grow or change enterprise information models.
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mamillary bodies

Two protuberances in the hypothalamus that resemble nipples. They are associated with memory-access functions, particularly accessing stored knowledge to interpret sensory input. When they are damaged, memory loss or amnesia of specific areas of knowledge occasionally results. Keywords: brain memory knowledge References: brain physiology neurons neuroscience
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MapReduce

MapReduce is a data access mechanism for Big Data. Frameworks such as Hadoop require data access mechanisms to allow users and developers to get at what's inside. [C-Net Google Reference] MapReduce is a programming model for processing large data sets, and the name of an implementation of the model by Google. MapReduce is typically used to do distributed computing on clusters of computers.
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Martinotti

A cerebral cell found in most of the layers upside down. Whereas most neurons have axons projecting away from the surface of the gray matter into the white matter, cells of Martinotti, like granule cells, point the other way. This adds a bidirectional flow of feedback impulses within the cerebrum. Keywords: horizontal cells cerebrum granule cells feedback association References: brain physiology neurons neuroscience
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meaning

Time and Space PerceptionMeaning is the fruit of understanding and the fuel of action. It is the contextual breaking apart and assembly of stimuli and knowledge. Meaning is neither immediate nor guaranteed, but is the quest and destination of the soul. Neither fraught with despair nor joy, meaning emerges, and all else follows. Meaning and understanding can only arise together at the junction of vision and thought in-situ. It cannot be conjured of nothing, nor can it survive in utter darkness, but thrives in the fertile soil of innate curiosity. Without meaning, there is no consciousness, no reason, no divinity, no humanity. Keywords: sememe     semantics     pragmatics      noise      idiom      experience      context      expressiveness      analysis References: chaos      comprehension      fuzzy logic      lexicography      linguistic strata      natural language      words/morphology
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meaningful

Face it – everything is meaningful! There are contexts in which a thing that is normally very meaningful may lose its importance. Meaningfulness is a measure of interest and relevance that we apply to the thing being considered. In any given context, almost everything in the universe is meaningless. Context draws small circles around that which is relevant, thereby excluding everything else. With context, we have a useful tool for focusing our attention on that which counts. Keywords: sememe semantics pragmatics noise idiom experience context expressiveness analysis References: chaos comprehension fuzzy logic lexicography linguistic strata natural language words/morphology
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mechanical brain

A man-made device that either performs some of the functions of the brain or represents the form of the brain or both. This term is usually used to refer to computers with advanced capabilities. Keywords: input data processing automata neurocomputing neuromorphism cybernetics thought computing References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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medulla

Medulla oblongata is the part of the brain stem between the pons and the spinal cord. Its main functions are control of breathing and circulation. Keywords: brain stem References: brain physiology neurons neuroscience
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memory

In a computer, a place where data is temporarily stored during processing; in a person, the place or places in the brain where knowledge is retained. Memory is often divided into categories such as short-term, procedural, declarative and episodic (see definitions). Keywords: short-term memory schemata recognition RAM mamillary bodies implicit representation gnostic forget flip-flop experience epistemology conceptual amnesia declarative memory episodic memory knowledge procedural memory hypermnesia association recall References: cognition comprehension context knowledge learning memory logic perception
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meta-knowledge

Knowledge about knowledge. Psychology and cybernetics are fundamentally meta-knowledge sciences because one must know about thinking and knowing before attempting to solve knowing and thinking problems. Clinical psychologists are often called to dig deep into mental circuitry (their own and others') to help solve problems. Intelligent machine designers have to do the same thing. Keywords: knowledge psychology cybernetics think thought uncertainty entropy References: associationism cognition inference knowledge taxonomy
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metabolism

The process of converting foodstuffs into energy for the body. Since the body is composed of cells, the primary agents and benefactors of the process are cells and their components. Without metabolism, cognition could not occur because the chemical components of the interactions in the brain are provided by metabolism. Keywords: ATP mitochondrion organelle References: brain physiology neurons neuroscience
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metadata

Metadata in DatabaseInformation about data: metadata describes characteristics of the associated data that may be useful to those who seek to find or understand it:
  • Descriptive metadata tells about the content of the data and it's place in the data universe
  • Lineage metadata tells where it came from and/or how it was derived
  • Governance metadata tells about its sources of record and, in an organization, who is responsible for it

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metadata management

Metadata in DatabaseA set of formal (stronger) or informal (weaker) processes for creating and maintaining data about content or knowledge. Metadata can describe key characteristics, such as topic, author, freshness and sensitivity of an organization's structured and unstructured information assets. Metadata can be embedded in the content, such as tagging in web pages, or held separately, such as ontologies that point to databases and files by URI or URL. The metadata can be used by systems needing the information to improve protection, integration, access, collaboration and sharing, linking, analysis, maintenance and retention. Data about content is needed for many cognitive computing processes.
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metaphor

A word or phrase used to represent something it is not or one or more characteristics of that thing. The presence of metaphor in human language is ubiquitous. While it often makes language more beautiful or poetic, it also can make understanding more difficult. Intentionally indirect forms of speech such as metaphor, irony, humor, deception and oblique reference have traditionally been nearly impossible for automated systems to correctly derive intent. Keywords: communication understanding
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metencephalon

The part of the brain consisting of the pons and the cerebellum. It is usually associated with the brain stem though the cerebellum is generally also considered as a cortex separate from the brain stem. Keywords: pons cerebellum References: brain physiology neurons neuroscience
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methodology

The study of method. Unfortunately, we humans have a tendency to misuse our words so much that they come to mean something other than what they started out meaning. Methodology has been applied to formal engineering processes (or methods) so often that it now refers to a menu of process or project management models. Keywords: formalism automata References: AI programming algorithms automata computing formalisms logic rules
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metonymy

Oval OfficeMetonymy s a form of speech that uses an individual or an attribute as a proxy for a larger object, group or class. Examples include John Doe for an unnamed person (typically male - Jane Doe for female), oval office for the US Presidency, suit for business executive, or the track for horse racing. Metonymy is broader than synecdoche, which is strictly using a part to describe the whole. Metonymy and synecdoche both twist context in ways that only the broader context of the surrounding language can help a person (or machine) discern the true intent of the speaker or writer. synecdoche
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microtubules

The largest of the three types of cytoskeletal components, microtubules provide structure to the cells such as neurons. They perform important roles in the different types of cells in which they exist, including motility for cells with cilia. Some researchers suggest cybernetic roles in neurons. Keywords: synaptic vesicle organelle MT intermediate filaments axoplasm cytoskeleton nerve fiber References: brain physiology neurons neuroscience
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MIMD

Multiple Instruction, Multiple Data is a parallel processing architectural standard with a few, several or many complex processors performing different operations at the same time. The results of these parallel computations are later assembled to determine a result. Keywords: systolic array SIMD parallel computing computing granularity References: AI programming algorithms automata computing formalisms logic rules
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mind

The part of us that thinks, remembers, learns and applies knowledge. This may be the brain, but many philosophers throughout history have suggested that the mind is different. The author of NeuroPedia believes the mind consists of the brain and the biological systems that contribute to perceiving the world and responding to perceptions. Keywords: discern brain consciousness psyche dualism References: cognition comprehension context fuzzy logic inference knowledge learning logic memory
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MIPUS

MIPUS RobotMobile Interactive Personal Utility System. MIPUS is a household android whose main domestic tasks include clearing the dinner table and washing the dishes. He is a personable robot and very introspective; in fact, you might say he is a true synthetic life form, if such a thing is possible. Keywords: robot robotics android ALife chaos References: AI programming cybernetics ethics genetics neural networks science fiction MIPUS the Robot Assistant MIPUS and Association Neurons Neural Conceptual Dependency Modeling Non-Random Synaptic Links The Fourth Dimension Weight Control for Knowledge  
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mitochondrion

Components of plastids and eucaryotic cells (including neurons) that convert energy to forms that are used to fuel reactions within and between cells. Their complex membrane structure, inside and out, enables them to metabolize sugars and fatty acids to efficiently produce ATP. Keywords: ATP metabolism organelle References: brain physiology neurons neuroscience
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mitosis

The process of cell division. Cell division involves extensive operation of filaments in polarizing the cell components to form two daughter cells. Keywords: differentiation cell brain development References: brain physiology neurons neuroscience
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model base

A set of structures similar to rules that are used in a decision support system (DSS) to help define problem and solution domains preliminary to attempting to guide decision makers toward a sound decision. Keywords: decision support system rule base knowledge base References: AI programming algorithms computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling system engineering
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modeling

UnderstandingContext.com is about modeling (Also spelled modelling) or designing mechanical models of the brain. Modeling means changing the scale and/or ingredients to get something that looks/acts like something else. While model railroading replicates trains in miniature, cybernetic modeling changes ingredients: instead of neurons and chaotic electrochemical interactions, cybernetic models generally use electronic devices. Keywords: GUI theory symbol software prediction perceptron distributed data type computer behavior cybernetics cognitive modeling computing References: AI programming algorithms computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling system engineering
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modularity

Modularity implies that programs consist of building-blocks of functions that can be assembled as needed to complete the structure. One big advantage of modular code is that computers are good at making copies of code. So if the code is truly modular, you should be able to reproduce it ad infinitum and apply it to any number of different systems with similar functions. This is where granularity comes in: the finer the granularity of code modules, the closer we can approach a "knowledge driven" technical ecosystem. Keywords: function code process program object References: algorithms automata computing formalisms
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modus ponens

An inference rule used to prove correctness or truth value of logical propositions. The form of the rule is this: If we know that when A is true, B is also true, and we know that A is true, then we can infer that B is true. In shorthand the conditions can be expressed A => B AND A. In more terse language we might say premise 1 is IF A THEN B and premise 2 is A. Keywords: modus tollens logic inference causal relations dichotomous logic determinism logical form References: comprehension formalisms information/entropy logic rules
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modus tollens

Another inference rule used to prove correctness or truth value of logical propositions. The form of the rule is this: If we know that when A is true, B is also true, and we know that A is not true, then we can infer that B is not true. In shorthand the conditions can be expressed A => B AND NOT A. In more terse language we might say premise 1 is IF A THEN B, premise 2 is NOT A, and the conclusion is, therefore NOT B. Keywords: modus ponens logic inference causal relations dichotomous logic determinism logical form References: comprehension formalisms information/entropy logic rules
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morpheme

In linguistics:  the smallest unique combination of letters forming a speech element having a syntactic or grammatical function that cannot be subdivided. Morphology  language natural language word sentence phonetics meaning morpheme
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morphology

The study of shape or form. Aristotle said that the mind is the "place of forms." Morphologies discussed in these volumes are the morphologies of cells and the brain itself, and linguistic morphology, or the ways in which chunks are assembled to make words. Keywords: physiology cerebrum word lexical language linguistics syntax References: linguistic strata natural language semantics syntax words/morphology
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mossy fibers

Axons that provide input to the cerebellum from other parts of the brain. They provide direct connections with both golgi and granule cells in the granular layer. The axons originate in the pons and spinocerebellar pathways. Each has 3 to 5 synapses with granule cell dendrites. Keywords: granule cells golgi cells cerebellum climbing fibers pons References: brain physiology neurons neuroscience
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MT

In UnderstandingContext.com MT can mean one of two things: 1) Microtubules, and 2) Machine Translation. Microtubules are also in the glossary. Machine translation is an automated way of converting text from one human language to another. MT is used as a sample domain for complex cognitive processes. Keywords: parsing microtubules interpretation natural language syntax semantics References: brain physiology neurons neuroscience
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multi-valued logic

Western societies have long relied on dichotomous logic championed by Aristotle and his successors. Oriental society has traditionally based reasoning on a different form of pragmatism that acknowledges shades of truth and partial falsehoods. Subjective or intuitive analysis of problem constraints often shows that while something is true under most circumstances, it may not be so true if something unexpected enters the equation. Some false things are truer than others. Using multiple truth or confidence values adds flexibility to the reasoning process. Keywords: quantifiers paradox fuzzy logic chaos non-determinism logic dichotomous logic fuzzy exception AI References: fuzzy logic knowledge representation logic taxonomy
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munge

Munge is a verb used with or without an object in computer slang to mean:
  • to manipulate (raw data), especially to convert (data) from one format to another, or
  • as a derogatory term meaning to poorly or tortuously transform disparate bits of information, or
  • to completely recode a routine, data structure or program.
It may be confused with or derive from mung (with its rank implications), or possibly vice-versa, or it may have been borrowed from the french "mange un mélange": to eat a mixture or medley.

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myelin

The "insulation" that forms around neural axons providing high resistance to electrical interference. The myelin is constituted of Schwann cells or glial cells (neuroglia). The color of these cells is white, thus the area filled with myelinated axons is called the white matter. Keywords: neurogliaform Ranvier, nodes of axon neuroglia white matter Schwann cell oligodendrocyte astrocyte References: brain physiology neurons neuroscience
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natural language

Human languages such as English and Swahili are called natural. I don't think languages are very natural, but compared to artificial languages like Morse code, Fortran, and music notation, natural languages are more than adequate for expressing what's on your mind. Keywords: sememe parsing MT expressiveness expression English acquisition language communication interpretation translation cognition aphasia Broca's area Wernicke's area References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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nerve

Nerves usually refer to the nerve cells or neurons near the skin that give us tactile sensitivity. Nerve can also refer to any neuron, but in modern usage, the tactile nerves are the subject. Keywords: neuroanatomy peripheral nervous system neuron perception References: brain physiology neurons neuroscience
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nerve fiber

An appendage or protrusion from the cell body of a neuron or nerve cell. Nerve fibers include axons (afferent and efferent), dendrites, spines and neurites (formative fibers). The elongation of these fibers is due, in part, to the filamentous components of the cytoskeleton. Keywords: microtubules arborization axon dendrite neurite spinal cord afferent efferent cytoskeleton brain circuitry References: brain physiology neurons neuroscience
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neural network

An artificial model of neurons in the brain usually consisting of a computer that has many interconnected nodes or cells represented as having two possible values, on or off, with links that have numerical values called weights. Electric potential flows in patterns dictated by the weights of links. Keywords: ANS node neuromorphism link linear discrimination distributed neuron perceptron neurode ART feedback firing weight connectionism References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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neurite

An immature neuron in the growth process. Keywords: nerve fiber brain development arborization dendrite axon neuron cell References: brain physiology neurons neuroscience
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neuroanatomy

1. The biological structure of the nervous system and its components. 2. The study of the same. Keywords: physiology parasympathetic brain central nervous system chaos iatric nerve References: brain physiology neurons neuroscience
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neurocomputing

The use of data-processing models based on neural networks or neuromorphic computer architectures. These models often attempt to imitate the structure and processes of human cognition. Keywords: NeuroPedia computing neuromorphism cognition mechanical brain References: AI programming brain physiology cybernetics neurons neuroscience
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neurode

A node in a neural network. Each neurode is interesting in and of itself because it can be the focus of inspection at two junctures: the reception of impulses from other neurodes, and the transmission of impulses to other neurodes. These junctures can be the focal points of learning algorithms through back-propagation or other formulae. Keywords: neuron linear discrimination node perceptron neural network link weight References: associationism connectionism neural networks
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neuroglia

Glial cells such as Schwann cells that are not neurons. They provide myelin sheaths or myelination for axons. They may also provide electrical and/or chemical insulation for other parts of neurons. Neurogliaform differ from glial cells in that they are actually neurons. Keywords: white matter Schwann cell myelin axon oligodendrocyte astrocyte Ranvier, nodes of neurogliaform References: brain physiology neurons neuroscience
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neurogliaform

A small cell type found in the superficial layers of the cerebrum. Keywords: stellate cells fusiform cells cerebrum basket cells white matter Schwann cell myelin axon oligodendrocyte astrocyte Ranvier, nodes of neuroglia References: brain physiology neurons neuroscience
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neuromorphism

Neuro: Pertaining to the brain or its cells.  Morph: shape. Neuromorphism describes cybernetic techniques of imitating the brain's form, organization, functions or capabilities in a computer model. It is assumed that by so doing, we can design more powerful computers. Keywords: physiology perceptron NeuroPedia ANS cybernetics neural network mechanical brain neuron neurocomputing References: AI programming algorithms brain physiology chaos cybernetics formalisms fuzzy logic knowledge representation modeling neurons neuroscience
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Neuron

Neurons are essential components of thought. A brain cell. Neurons have many different shapes, sizes and, presumably, different functions, depending on their location in the brain and their structure. Neuron shape may be less spindley than most pictures depict. In fact, Volume 2 shows neurons with a more ink-blot than tree-like shape. Keywords: adrenergic physiology permeability output NeuroPedia neuromorphism neurite neural network nerve gnostic firing cytoplasm cortex cell axoplasm activation action potential differentiation synapse soma axon dendrite neurode References: brain physiology neurons neuroscience
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NeuroPedia

The contents of the Understanding Context blog were originally created in Asymetrix ToolBook as NeuroPedia. A compendium of information on human and mechanical brains. Encyclopedia of neurocomputing — Neurotic pediatrician — Brain in feet — Foot in brain — Neurosis caused by kids — Neurosis caused by sore feet — Neurosis caused by encyclopedia — Neurosis caused by hypermedia encyclopedia of neurocomputing ... You choose! Keywords: brain neuron information neurocomputing neuromorphism References: AI programming algorithms brain physiology chaos cybernetics formalisms fuzzy logic knowledge representation modeling neurons neuroscience
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neurotransmitter

A type of chemical whose release from one neuron effects a change in electrical potential at a synapse that reaches another neuron. Some neurotransmitter chemicals are acetylcholine, norepinephrine and dopamine. Keywords: synaptic vesicle quantal release norepinephrine local potential Amines adrenergic activation acetylcholine cholinergic dopamine E/I action potential synapse References: brain physiology neurons neuroscience
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NLP

Natural Language Processing: using automated processing to do something useful with human words, phrases, sentences and more. Today there are many branches of NLP: automated translation, summarization, smart search and question answering. We are interested in automated dialog.
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node

A single element in a network such as a local area network, a semantic network or a neural network. A node is usually represented by a symbol such as a circle or a piture of the thing at the node (such as a computer terminal or a fired neuron). Keywords: relation neurode neural network ANS representation symbol weight threshold link References: associationism chaos connectionism learning neural networks
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noise

In a cognitive sense, noise is the bulk of information that enters our senses during the course of a given time segment, and gets filtered out as being useless information. If we were not able to filter out noise, it is very likely that we would all suffer from cognitive overload within the first few moments of becoming sentient. Keywords: information perception entropy meaningful expressiveness References: chaos inference information/entropy probability
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non-determinism

Producing unpredictable results. Non-deterministic programming techniques are used to implement fuzzy logic and even simulate chaos. Non-deterministic algorithms rely largely on random, accidental or unpredictable processes. Many suggest brain activity is non-deterministic. Even the best automatic randomizing algorithm is ultimately predictable, so pure non-determinism has yet to be realized in computational systems. Keywords: hypertext fuzzy dichotomous logic chaos multi-valued logic fuzzy logic determinism logic References: Minsky, 1986 fuzzy logic inference information/entropy knowledge logic perception
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noosphere

Vladimir Vernadsky (background) and Teilhard de Chardin (Bio), describe a noosphere: the "sphere of human thought".  The noosphere contains the facts, fictions, metaphors and illustrations to which we assent: the truth and the fictions. See my February 2013 post.
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norepinephrine

Transmitter (also called noradrenaline) liberated by most sympathetic nerves. Keywords: acetylcholine neurotransmitter action potential E/I synapse adrenergic amines dopamine References: brain physiology neurons neuroscience
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normalization

ERD - Entity Relationship DiagramA process used in modeling data, especially in relational databases, to minimize redundancy. Data normalization techniques can save space and improve data quality by simplifying changes to data. See Holowczak's tutorial on how to do it, and Margaret Rouse on what it is. Relational database normalization relies on Primary and foreign keys that link tables together in one-to-one or one-to-many relationships.

First normal form (1NF) is a minimal level of normalization in which the database:

  • contains any number two-dimensional tables with rows and columns named to represent the core object;
  • each table's columns contain data on the attributes of the core object and the column names usually name the attribute;
  • each row or record in each table represents a unique instance of the core object or attribute and must contain at least one value different from any other row (no duplicate rows are allowed);
  • All entries in any column must be of the data type (date fields must contain valid dates and amount fields must contain valid numbers).

Second normal form (2NF) is an intermediate level of normalization in which each column in a table that is not a determiner of the contents of another column, must itself be a function of the other columns in the table. For example, in a "Purchases" table with columns containing "Customer ID", "Product", and "Price", the price would be a function of the customer ID and the specific product and may be derived from a separate "Prices" table.

Third normal form (3NF) is the defacto standard for transactional database modeling (reporting databases are often "denormalized"). 3NF states that all columns in a table not dependent on the primary key should be removed from the table, and placed in a separate table or eliminated. Another way of putting this is that only foreign key columns should be used to reference another table, and no other columns from the parent table should exist in the referenced table.

   
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object

Something. The thing may be physical or abstract. We know it is an object if it has a clear definition that usually includes boundaries and one or more properties. Abstract things are more difficult to segregate into discrete objects, but it is necessary to do so in object-oriented system design. In object-oriented systems, an object is a package of information and descriptions of its manipulation all wrapped up together. Keywords: relation OOPS modularity interaction existential dimension categorize class property object-oriented polymorphism composition inheritance decomposition abstraction boundaries References: AI programming algorithms automata computing formalisms logic rules
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object-oriented

Any of a set of system design and development techniques that treats data elements in a system as objects with inherent properties. See the list of cross-reference words below for characteristics usually associated with object-oriented design and development. Keywords: property polymorphism OOPS existential code categorize object class inheritance abstraction composition decomposition References: AI programming algorithms automata computing formalisms logic rules
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objective

Objective can be a noun meaning goal or aim. In search, the objective refers to what you want to find. When 'objective' is an adjective, it means a viewpoint or decision based solely on logic. Because all complex human cognitive activities involve feedback from the amygdala, it may be impossible to remove hormones from any human viewpoint or decision. Thus absolute objectivity may not be possible for humans. Keywords: logic subjective emotion amygdala anxiety decision cognition response References: cognition inference knowledge logic
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ODBMS

Database IconObject Database Management System: is object-oriented database system software that treats and models data as objects. Like OO programming systems, ODBMS' provide classes of objects and the inheritance of class properties and methods by subclasses and objects to define the links between different data entities. Malcolm Atkinson et al got the ODBMS ball rolling in their in 1995 paper: The Object-Oriented Database System Manifesto, suggesting database models that seamlessly inter-operate with object-oriented programming languages such as Smalltalk. Database systems typically manage persistence, concurrent threads or processes, secondary storage, recovery and support ad hoc queries. ODBMS' add complex objects, object identity, encapsulation, types or classes, inheritance, overriding combined with late binding, extensibility and computational completeness (see ODBMS Definition).
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olfactory

The sense of smell and the central nervous system component that enables us to distinguish between different smells. The olfactory system is associated with the paleocortex or that part of the brain which is said to have developed earliest in the evolution process. This sense is more developed in animals than in humans. Keywords: sense perception input References: brain physiology neurons neuroscience
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oligodendrocyte

A type of glial cell found in the brain that does what Schwann cells do in the peripheral nervous system: insulate axons from external electrical impulses. Without this insulation, spurious electrical activity could disrupt the normal patterns of electrical flow necessary to facilitate cognition. Keywords: neurogliaform myelin astrocyte Schwann cell neuroglia axon action potential References: brain physiology neurons neuroscience
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ontology

An ontology is a set of associated concepts useful for both interpretation and action. Good quality ontologies will be the underpinning of the most intelligent systems in the coming age of knowledge. The Free Online Dictionary states that "In both computer science and information science, an ontology is a data model that represents a set of concepts within a domain and the relationships between those concepts. It is used to reason about the objects within that domain.  
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OOPS

Object-Oriented Programming Systems. One of the world's most appealing acronyms. Keywords: data-driven object object-oriented logical form References: AI programming algorithms automata computing formalisms logic rules
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Open Web vs. Deep Web

The internet has been inhabited by protocols for browsers to read content in HTML (HyperText Markup Language) that create a massive web of interconnected content collectively known as the "world-wide web" (www) or just the "web". The open part is content that is not protected by passwords, and thus accessible to anyone. Some pages on the open web do not permit search-engine access for crawling and indexing, thus making the content harder to find, but nevertheless accessible. TechTarget tells us that "Deep Web content includes information in private databases that are accessible over the Internet but not intended to be crawled by search engines. For example, some universities, government agencies and other organizations maintain databases of information that were not created for general public access. Other sites may restrict database access to members or subscribers." (definition: deep web) Links Handling High Volume, High Velocity Data
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organelle

A component of a cell that is functionally complex enough, albeit on a smaller scale, to be compared to an organ of the body. Nerve fibers are sometimes called organelles, but microtubules may fit the description better. While organ functions are governed by tissues, organelle functions are often governed by the properties of their constituent membranes. Examples of organelles are in the cross-references. Keywords: axon dendrite mitochondrion microtubules synaptic vesicle metabolism References: brain physiology neurons neuroscience
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organism

A living thing with organs. A single-celled living thing such as a paramecium or amoeba is not an organism. Many dictionaries include in the definition of organism nonliving things that resemble living organisms in complexity of structure or function. Keywords: brain intelligence References: brain physiology neurons neuroscience
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output

In computing systems, output is what is delivered to peripheral devices as a result of processing. Most output goes to a monitor. Formerly teletypes were used. Printers and modems also accept output. In the brain, neurons have outputs individually through axons via synapses to other neurons. Collective output of the nervous system includes thoughts, words and actions. Keywords: code afferent input axon neuron efferent References: algorithms automata computing
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overloading

Digital Data StreamSome object-oriented programming languages permit reuse of the same function name to perform different functions in different contexts. This polymorphism mirrors polysemy which creates ambiguity in human languages. Function overloading or method overloading, found in programming languages such as Ada, C++, C#, Delphi, D, Java, and Swift, allows creating more than one method with the same name that differ from each other in the type of the input and the output of the function. In operator overloading, or ad hoc polymorphism, different operators have different implementations depending on their arguments. In either case, programmers are required to keep these things straight in their minds and documentation to ensure proper functioning code.
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overshoot

1) In sports, to place the ball or puck outside the boundaries of the goal by applying too much or misdirected energy 2) In neuroscience, reversal of membrane potential during strong excitatory impulses. The resting potential is about -70 millivolts, and the threshold of activation is about -40 millivolts. A strong spike can actually push the potential within a cell out of the red into the positive charge zone. Keywords: hyperpolarization E/I action potential References: brain physiology neurons neuroscience
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OWL

Web Ontology Language (dyslexically) - A model for semantically indexing content, particularly on the World Wide Web, in an ontological framework (RDF).
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paleo-cortex

The paleo-cortex is the oldest part of the brain (see medical dictionary). It is where we process odors - the olfactory processor in the brain.
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paradigm

A pattern for doing or thinking about something. Paradigms can be based on examples, models, rules of thumb or compiled knowledge. Today the word has assumed the negative connotation of an outmoded approach or perspective. But paradigms can be good too. Keywords: hypertext OOPS framework References: associationism cognition inference knowledge taxonomy
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paradox

A set of circumstances in which competing objectives or contradictory factors make a decision very difficult. Paradoxical propositions defy logic and require complex reasoning. Without multi-valued logic, resolving paradoxes is often impossible, but with it, one can choose the "lesser of two evils" or the course that delivers the most desireable outcome. Keywords: conclusion logic reasoning reason fuzzy logic multi-valued logic References: context information/entropy logic
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parallel computing

Computational techniques that decompose problems into tasks and threads that can be computed on different machines or processing elements at the same time. Keywords: SIMD MIMD architecture systaltic array granularity distributed systolic array References: AI programming algorithms automata computing formalisms logic parallel computing rules
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parasympathetic

The parasympathetic nervous system, part of the autonomic nervous system, links each of the body systems and organs with the brain. Feedback from the body is interpreted and activates involuntary responses such as a change in the chemical balance. Keywords: peripheral nervous system autonomic nervous system central nervous system neuroanatomy References: brain physiology neurons neuroscience
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parsing

A computerized method of analyzing strings or streams of symbols. Since human language can be written using strings or streams of symbols, parsing may seem an appropriate way for computers to treat human language. In fact, it is. The technologies computers use to interpret computer languages, which must obey all their own rules, must be fundamentally different that parsers for human languages which regularly deviate from thier own rules. Keywords: ATN natural language analysis MT symbol input interpretation References: comprehension fuzzy logic lexicography linguistic strata natural language words/morphology
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pathology

The study of the causes of diseases or abnormalities. Pathlogy has been a great help in learning about functions performed by different parts of the brain because, by seeing what goes wrong when a certain part is damaged, we can infer that part's function. Keywords: psychosis dementia brain aphasia tactile agnosia References: brain physiology neurons neuroscience learning pathology psychology
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pattern

The form of something. Patterns can be strings of letters or events, 1-dimensional lines, 2-dimensional images, or multidimensional phenomena. A theory of everything suggests that everything is a pattern of vibrations in the universal mass. Patterns can be useful in computing in that they provide a basis for matching (pattern recognition). Keywords: binding form structure function References: cognition comprehension context fuzzy logic inference knowledge logic pattern recognition perception
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perception

Accumulation of information using the senses of sight, hearing, smell, taste and touch. Perception sometimes refers to cognitive processes independent of the senses (i.e. extrasensory perception) but usually refers to sensory activities. Sensory knowledge comes from perception of object properties. Keywords: extra-sensory comprehension stimulus spinal cord somatosensory cortex sentient sensory reflex receptive field RAS polysemy olfactory noise nerve image processing filtering feature expressiveness expression disambiguation attention arousal cognition sense interpretation ambiguity learning recognition cue intelligence binding input References: cognition comprehension context fuzzy logic inference knowledge logic perception
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perceptron

A probabilistic model for information storage and organization in the brain. This model, proposed in the 1950s by Rosenblatt, is the granddad of modern neural networks. It consists of single cells that can adapt or change their processing characteristics through repeated exposure to an input (learning). Keywords: neurode neural network ART modeling neuromorphism References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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peripheral nervous system

The PNS consists of the craniospinal nervous system that controls voluntary muscle movements and the autonomic nervous system that controls involuntary muscle movements. The PNS is separate but integrated with the central nervous system that performs the cognitive processing prior to voluntary movements. Keywords: corticospinal tract autonomic nervous system parasympathetic central nervous system nerve spinal cord References: brain physiology neurons neuroscience
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permeability

Membrane property allowing passage of substances into and out of cells. Keywords: neuron action potential pump References: brain physiology neurons neuroscience learning pathology psychology
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personality

One's character and mannerisms. Introspection leads to an understanding of one's self. The term "personality" suggests that without this element of humanity, there may not be substance to make a body a person. Keywords: frenetic introspection phrenology References: chaos
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phoneme

The smallest unique units of speech sound speakers of a human language use to form morphemes, words, and sentences. Each language has its own set of between about 20 and 60 such unique sounds, but the set of all phonemes used by all humans is not likely to exceed 80 to 100. Phonemes typically do not bear meaning, but assume meaning as they are interconnected with other phonemes. language natural language word sentence phonetics meaning morpheme
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phonetics

The analytical science of categorizing speech sounds, their production in humans and mechanical contraptions, and their representation in written symbols.


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phrase

  1. Parse Tree ActorA a sequential group of two or more spoken or written words that form part of a sentence, impacting the interpretation of the surrounding language
  2. An idiom with commonly understood meaning and usage
  3. A complete sentence with only a single phrase
  4. A syntactic structure such as: "a noun phrase composed of determiners, adjectives, subordinate noun phrases and/or prepositional phrases"
natural language word sentence
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phrenology

The study of the shape of the head to determine personality or character. This turn-of-the-century pseudoscience is not taken seriously by many any more. It is akin to physiognomy: the art of determining personality by the shape of the face. Keywords: psyche behavior introspection personality frenetic References: cybernetics ethics genetics science fiction
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physiology

The study of human body structure. NeuroPedia explores brain physiology in order to synthesize a similar computer physiology. Another word for the study of structure is morphology. Our new computer structure can be described as neuromorphic. Keywords: morphology brain Brodmann neuroanatomy neuromorphism neuron References: brain physiology neurons neuroscience
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polymorphism

A property of OO systems in which the representation or form of objects is dynamic while the function or behavior of those objects is specified, inheritable, and shared between objects even if the objects themselves are of diverse form. Polymorphism permits a common message vocabulary and semantics. Keywords: object-oriented object class property composition inheritance decomposition abstraction boundaries References: AI programming algorithms automata computing formalisms logic rules
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polysemy

Multiple meanings. Polysemous words, phrases, sentences and other utterances exhibit ambiguity. Polysemy is ubiquitous so disambiguation is a continual process in interpreting communications. Context is one of the best tools available for resolving polysemy and correctly interpreting things. Keywords: anaphora ambiguity context disambiguation perception cognition communication References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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pons

Part of the midbrain that serves as a pathway for nerve fibers between the spinal cord and the cerebral and cerebellar cortices (that's plural for cortex). Keywords: mossy fibers brain stem metencephalon References: brain physiology neurons neuroscience
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possibility

Something that exists within a framework of laws controlling phenomena, such as the physical universe. We have reason to believe that the laws of physics govern the behavior of things in the universe. If this is true, and if there is no mystical "random" law breaker out there, then there is a threshold above which anything can happen (possibility) and below which nothing can happen (impossibility). This threshold, governed by the laws of physics, known and unknown, in aggregate, may or may not exist. If it does not, the there is no such thing as impossibility. It would be logical to conclude that if nothing is impossible, then the term "possibility" becomes unnecessary. I choose to cling to a notion of order in which the threshold of possibility exists, and can be relied upon to prevent the impossible from ever happening.
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possible

Any event or occurence which can happen. In threshold logic, the possibility of any event falling either above (possible) or below the threshold (impossible); nothing can straddle the line. Threshold logic applied to possibility is context-governed; consequently, some events may be possible in some contexts and impossible in others. If nothing is impossible, this does not apply. Keywords: impossible probability References: chaos inference logic probability
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pragmatics

The study of deep meaning and the impact of context on meaning. Phonology, morphology and syntax are closer to the surface of language understanding in that they are tied to the shape and ordering of the words independent of meaning. Deep understanding requires semantic, pragmatic and world knowledge. Keywords: language linguistics word semantics syntax analysis meaningful References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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prediction

A process of guessing the future. In business, as in life, better guesses facilitate preparation for the future by building credible expectations. Prediction is a fundamental cognitive process. As part of prediction, we develop models of probability in our minds and compare them to guess which of all possible outcomes is most likely. Keywords: theory expectations cognition anxiety learning logic probability modeling References: algorithms automata chaos computing formalisms inference logic rules
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premise

A stated or assumed fact used as a basis for establishing a logical proposition or forming a conclusion in human reasoning or logical argument.
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probability

The science of determining likelihood based on existing conditions compared to historical conditions. Probability theory is used to predict the weather based on observations and comparisons with past phenomena occurring after similar conditions. Probability theory is used in AI computing to improve chances of reaching a solution by cuing, or increasing our confidence in the solution. Keywords: theory statistical analysis standard deviation sample space range prediction possible impossible analysis stochastic random chaos dead man's hand References: chaos inference logic probability
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problem

Anything for which a person (or computer) may seek a solution. Problem is a very ambiguous word. It almost always carries negative implications, but it often refers to a good business or automation situation that requires a solution. Keywords: algorithm heuristic domain References: automata logic modeling pathology physics
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procedural knowledge

Knowledge of how to do things. This is the chunk of our memory where the motions of crawling and playing piano are stored (along with every other voluntary muscle movement). Keywords: knowledge declarative knowledge episodic knowledge intelligence References: associationism cognition inference knowledge memory taxonomy
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procedural memory

This is the knowledge we use to do things such as rolling over in bed and manufacturing spacecraft. Naturally, the more technical or complex the task becomes, the more declarative (as in object assembly) and possibly episodic (as in skilled sports) memory contributes to our ability to perform. Keywords: short-term memory recall episodic knowledge declarative memory episodic memory knowledge memory References: associationism cognition inference knowledge memory taxonomy
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process

Two meanings or process appear frequently in UnderstandingContext: 1) axons and dendrites are called nerve processes, meaning branches; 2) a set of steps performed by a person or machine (or both) to accomplish something is called a process. Keywords: robust symbol software modularity function design data-driven code branching argument analysis algorithm References: associationism cognition inference knowledge memory taxonomy
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production system

A computational system or part of a system that contains any number of production rules (a rule that provides a defined result or action for a defined condition or logical statement), along with a database of state information and a procedure for invoking the rules. In production systems, the process of invoking rules (usually an arbitrary process) is called "firing" – just like in the brain. At the time of this blog, these systems are often called "rules engines". Keywords: expert system rule inference logic References: AI programming algorithms automata computing formalisms logic rules
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program

  1. Digital Data StreamA preestablished process for doing something (the twelve-step program)
  2. The act of writing instructions for a computer
  3. A set of instructions for a computer or a computer application
  4. A large, deep hole into which a government can dump money indiscriminately
  5. A show on the television
  6. A regimen
I googled "program" and from the definition I got (below) I want to focus on the first one under verb:
noun: programme; plural noun: programmes; noun: program; plural noun: programs
  1. a planned series of future events, items, or performances.  "a weekly program of films"
    synonyms: schedule, agenda, calendar, timetable; More order of events, lineup "our program for the day"
    • a set of related measures, events, or activities with a particular long-term aim.  "the nuclear power program"
      synonyms: plan of action, series of measures, strategy, scheme"the government's reform program"
  2. a sheet or booklet giving details of items or performers at an event or performance.  "a theater program"
    synonyms: guide, list of performers, cast list, playbill "a theater program"
  3. a presentation or item on radio or television, especially one broadcast regularly between stated times.  "a nature program"
    synonyms: broadcast, production, show, presentation, transmission, performance, telecast "a television program"
    • dated: a radio or television service or station providing a regular succession of programs on a particular frequency; a channel.
  4. a series of coded software instructions to control the operation of a computer or other machine.
verb: program; 3rd person present: programs; past tense: programmed; past participle: programmed; gerund or present participle: programming; past tense: programed; past participle: programed; gerund or present participle: programing
  1. provide (a computer or other machine) with coded instructions for the automatic performance of a particular task.  "it is a simple matter to program the computer to recognize such symbols"
    • write computer programs.  "I've programmed for 25 years and have used many languages"
    • input (instructions for the automatic performance of a task) into a computer or other machine.  verb: programme; 3rd person present: programmes  "simply program in your desired volume level"
    • cause (a person or animal) to behave in a predetermined way. "all members of a particular species are programmed to build nests in the same way"
  2. arrange according to a plan or schedule. "we learn how to program our own lives consciously"
    synonyms: arrange, organize, schedule, plan, map out, timetable, line up, slate "they programmed the day well"
Keywords: tools modularity design data type code software computer References: AI programming algorithms automata computing formalisms logic rules
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programming

Digital Data StreamThe art of translating human thought patterns into automated computer code. I didn't say it was useful. Much of it is not. But the stuff that is can be pretty amazing. "Rather than increasing the number of kids who can crank out thousands of lines of JavaScript, we first need to boost the number who understand what code can do. As the cities that have hosted Code for America teams will tell you, the greatest contribution the young programmers bring isn't the software they write. It's the way they think. It's a principle called "computational thinking," and knowing all of the Java syntax in the world won't help if you can't think of good ways to apply it." (Mother Jones)

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programming language

Computer Program FlowA formal language with its own syntax, reserved words (vocabulary) and tools for interpreting or compiling, that allows programmers to author a set of instructions that can be used to accept input, perform processes, and deliver various kinds of output. High level Programming languages are more readable and easier to compose, like human language, and low level languages like assembler and Op Code are less human readable, but great for folks made of highly conductive metals and silicon. The code that specifies the algorithms written in the languages can be interpreted or compiled into executable instructions for a computer.
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property

A possession. In cybernetics, particularly in object-oriented system design, we describe things as objects. One of the ways we know the difference between one object and another is to compare their respective properties. In physical objects, color, shape, size, smell, and mobility are properties an object may possess. Abstract objects may possess properties such as meaning, duration, sequence, context, origin, and goal. Boundaries are a kind of property. Keywords: feature polymorphism existential boundaries object object-oriented descriptive relations References: comprehension context inference knowledge logic perception
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proposition

A formal representation of declarative, procedural or episodic knowledge. Normally these representations use natural language or narrative logic to express knowledge in a way that resembles perceptible facts about the real world. Many or all propositions can be abstracted to form rules of inference. Keywords: conclusion equation fact rule exception knowledge logic inference learning rule base References: cognition comprehension context fuzzy logic inference knowledge logic perception
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psyche

1. A beautiful nymph who personified the soul (Venus hated her – Cupid loved her). 2. The human soul (this is what Aristotle wrote about in On the Soul). 3. The mind, especially as a biological system that can send and receive signals to and from all parts of the body to help it adapt to the immediate environment. Keywords: imagination mind consciousness psychology phrenology dualism References: cognition comprehension context fuzzy logic inference knowledge logic perception psychology
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psychology

The study of the psyche, human thought, and the pathology of social interaction as well as the interaction of physiology and cognition to produce the range of human responses. Keywords: psychosis psyche meta-knowledge cognition think References: cognition comprehension context fuzzy logic inference knowledge logic perception psychology
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psychosis

A mental illness often caused by spending too much time with a computer. Experts suggest this psychological disease is transmitted through keyboards or infected mice, but some theories equate it with tiny rays of unknown origin emitted by monitors. These rays pass through the eyes and attack the brain. Keywords: psychology pathology References: brain physiology neurons neuroscience learning pathology psychology
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pump

Mechanism that actively transports chemicals through permeable membrane. Keywords: E/I action potential permeability References: brain physiology neurons neuroscience
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Purkinje

The largest of the cell types in the cerebellum, these massive cells have their cell bodies packed together in a single layer while their axons extend down through the granular layer into the white matter, and their dendrites extend up through the molecular layer. Keywords: pyramidal cells cerebellum climbing fibers stellate cells golgi cells basket cells granule cells References: brain physiology neurons neuroscience
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pyramidal cells

A large garden variety neuron type found ubiquitously in the cerebrum. Their apical form gives them their name. They tend to have many dendrites and extensive branching. Giant pyramidal cells correspond to Purkinje cells in the cerebellum. Keywords: horizontal cells cerebrum Purkinje cerebrum References: brain physiology neurons neuroscience
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qualitative insight

Language and DialogUnlike quantitative metrics and numerical performance indicators, quality is described in natural language, often in extended narrative text. Its sources are often social media, surveys, face-to-face interviews (dialog) and focus group transcripts. Manually assembling qualitative data to derive insight can be more difficult than quantitative data. This is why cognitive computing with natural language processing capabilities are valuable.
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quantal release

Secretion of quanta (multimolecular packets) of neurotransmitter through presynaptic membrane. Keywords: action potential E/I neurotransmitter impulse References: brain physiology neurons neuroscience
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quantifiers

In formal logic we have two kinds of qualifiers, existential and universal. The backwards capital E is the existential quantifier. It means 'there are some' or 'sometimes' and it modifies the variable it precedes. The inverted capital A is the universal quantifier. It means 'for all' or 'always' and it modifies the variable it precedes. The universal quantifier followed by a negated expression means 'never.' Be careful with the universal quantifier. Truly fuzzy systems imply frugal use or non-use of always or never. Keywords: logic formalism equation multi-valued logic reasoning References: algorithms automata computing formalisms logic rules
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quantitative insight

Reporting, Analytics and Business Intelligence relay heavily on numerical data as performance indicators. Visulaizations of quantitative data as trendlines, bar graphs, pie charts, heat maps, topographies and scatter graphs can help deliver insights from numbers. This is a contrast to qualitative insight normally derived from non-numeric information such as natural language text.
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RAM

Random Access Memory. Volatile memory based on integrated circuits filled with bistable transistor assemblies called "Flip-Flops." RAM is where programs and the data or information they use reside while your computer is turned on. When you turn it off, whatever was in the computer's RAM goes away unless there is a power source (such as a battery) that actively maintains the charge and refreshes the current in the RAM. Keywords: short-term memory memory computer information References: computing memory
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random

Flower FractalSomething that is devoid of a regular pattern. In the mathematical definition, it is random because we don't yet understand the laws or formulas that govern it. In other definitions, it is due to its immunity to any law which would force it into a repeating sequence that would constitute a pattern. The existence of the lawless form of randomness is purely theoretical since there is no way to prove that anything is infinitely irregular or unpredictable. Small-scale quasi-randomness (as opposed to pure randomness) is a useful tool, particularly in game theory. Does the Copenhagen Interpretation prove that there is such a thing as randomness?
Definitions References
self-similarity    fractalchaos
continuum    probabilityinference
stochastic    chaoslogic
dead man's hand probability
That's so Random! The Random Hamlet Non-Random Synaptic Links
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range

1) The place where I am seeking a home 2) The appliance on which I prepare my dinner 3) Range is the scale of distance between the lowest and highest values obtained from a sample distribution. Because range involves the extreme ends of the scale, it is extremely unstable. It is useful, however, for segregating anomalous from exceptional data. In a filtering system, setting appropriate ranges enables automatic systems to flag out-of-range values, which can be of great value to the analyst. Keywords: sample space statistical analysis probability standard deviation equation composition constraint References: algorithms automata computing rules
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Ranvier, nodes of

Segments along the length of axons wrapped by single Schwann cells. The regular widening of the cells resembles the segments of an arthropod. Glial cells insulate axons from external electrical interference. Keywords: neurogliaform neuroglia myelin axon action potential E/I References: brain physiology neurons neuroscience
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RAS

Reticular activating system. The RAS is a network of neurons extending from the brain stem to the cortex (primarily medulla, pons, midbrain) that filters incoming sensory stimuli, allowing attention to focus on critical inputs and ignore noise. Keywords: filtering attention perception cue brain stem References: brain physiology neurons neuroscience vision
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RDF - Resource Description Framework

RDF is a semantic model using "triples" for data storage, access and interchange, supporting data merging across different schemas. The triples model creates a directed graph that can grow supporting the evolution of schemas over time without requiring all the data interfaces to be changed. The expressiveness of RDF is in the URIs that name the relationships between things as well as the two ends of each link, allowing relational database content and less structured content to be combined, accessed, and shared across different applications. The collection of RDF triples becomes a directed, labeled graph, where the edges represent the named links between each pair of resources, and the resources themselves forming the graph nodes. OWL Post
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reason

1) Something only slightly better than an excuse. 2) The ability to correlate information, including possibly conflicting information, to arrive at a conclusion that is based on logical or insightful analysis of the interaction of constraints or parts of the problem. Keywords: paradox intelligence thought inference logic reasoning References: cognition comprehension context fuzzy logic inference knowledge logic perception
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reasoning

The cognitive process of making inferences about data to interpret an observation or situation based on past, present and/or future constraints that may have some influence on the outcome. This application of diverse constraints coupled with the temporal aspect make reasoning a very complex process. Keywords: stochastic quantifiers paradox logorrhea equation discern decision conclusion conceptual inference association correlation syllogism thought reason References: cognition comprehension context fuzzy logic inference knowledge logic memory perception psychology
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recall

The process of accessing knowledge in short or long-term memory to find if a certain object, event or concept is present. If it is in memory, it will be recognized wholly or independently. If it resembles things in memory, it will probably be categorized and possibly stored for later recall if it is important. Keywords: recognition forget memory declarative memory episodic memory knowledge procedural memory short-term memory References: learning memory
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receptive field

Part of a perceptual pathway such as part of the retina, that directly influences neuron firing. Keywords: perception cognition References: brain physiology neurons neuroscience vision
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recognition

If you've cognized something once, it is possible you will encounter it again and recognize it. Whether you can identify, describe or explain it is not the issue. The issue is that you once encountered it in a cognizant way, and it stuck enough that you can recall the prior experience. Keywords: discern linear discrimination expectations cue communication perception binding interpretation memory recall References: cognition comprehension context fuzzy logic inference knowledge logic pattern recognition perception
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recursive

1. A process that calls itself, creating nested instantiations as often as necessary to yield a result. 2. A grammar formalism characterized by productions that revert inward to arbitrary or potentially infinite levels of nesting. Keywords: context-free context-sensitive grammar References: algorithms automata computing formalisms logic rules
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reflex

Responses to stimuli that are involuntary. The classic reflex is the knee-jerk response to a tap with a hammer. Reflexes are processed in the spinal cord rather than in the higher-level motor processing centers. Muscle memory, in which a part of the body has done a thing so many times that it can repeat the action without concentration, grows to behave like reflexes. Keywords: stimulus laughter kinesthesia expression spinal cord integration perception response instinctive References: brain physiology neurons neuroscience
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register

Register as a verb can be used like "remember". A register (noun) can be a set of digital "locations" that, combined, are treated as a base unit of computing. A byte register is 8 bits in length,  a word 2 bytes, a doubleword 4 bytes and a quadword 8 bytes or 64 bits (commonly in use as a personal computing standard at the time of this writing). The Tortall YASM Manual tells us about Intel CPU architecture: The 64-bit x86 register set consists of 16 general purpose registers, only 8 of which are available in 16-bit and 32-bit mode. The core eight 16-bit registers are AX, BX, CX, DX, SI, DI, BP, and SP. The least significant 8 bits of the first four of these registers are accessible via the AL, BL, CL, and DL in all execution modes. In 64-bit mode, the least significant 8 bits of the other four of these registers are also accessible; these are named SIL, DIL, SPL, and BPL. The most significant 8 bits of the first four 16-bit registers are also available, although there are some restrictions on when they can be used in 64-bit mode; these are named AH, BH, CH, and DH. The 80386 extended these registers to 32 bits while retaining all of the 16-bit and 8-bit names that were available in 16-bit mode. The new extended registers are denoted by adding a E prefix; thus the core eight 32-bit registers are named EAX, EBX, ECX, EDX, ESI, EDI, EBP, and ESP. The original 8-bit and 16-bit register names map into the least significant portion of the 32-bit registers. 64-bit long mode further extended these registers to 64 bits in size by adding a R prefix to the 16-bit name; thus the base eight 64-bit registers are named RAX, RBX, etc. Long mode also added eight extra registers named numerically r8 through r15. The least significant 32 bits of these registers are available via a d suffix (r8d through r15d), the least significant 16 bits via a w suffix (r8w through r15w), and the least significant 8 bits via a b suffix (r8b through r15b). The figure below summarizes the full 64-bit x86 general purpose register set.

x86 General Purpose Registers

x86 General Purpose Registers

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regular

A grammar formalism characterized by its deterministic description of how things work. A regular grammar is the most restrictive and least flexible formalism. Keywords: grammar context-free context-sensitive References: algorithms automata computing formalisms logic rules
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relation

A named connection between two or more things. A connection without a name is a link. By adding a name to a connection, the meaning of the connection becomes clear. Associations between things can be described using explicit relations. Relations come in many shapes, including hierarchical and causal. Keywords: experience arity link association causal relations hierarchical relations explicit representation node object References: associationism cognition connectionism inference knowledge taxonomy
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relay

Many neurons serve to relay impulses across great distances and between different areas of the brain. Besides having long processes, these cells are capable of revitalizing signal strength (like an electronic signal repeater) to maintain their intensity despite the distance. Keywords: correlation action potential E/I References: brain physiology neurons neuroscience
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representation

A method of symbolizing information in a system. Knowledge is represented in our brain by the pattern of links (associations) between neurons. In designing computational systems, the representation of information or knowledge in the system becomes the underlying structure of the system. No taxation without representation! Keywords: node implicit representation dimension digital analog symbol symbolic logic information knowledge representation References: context knowledge representation logic taxonomy
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response

Reaction to a stimulus or stimuli. Biological responses to stimuli range from electrical activity in the brain, to changes in the cardiovascular rate, to accelerated perspiration or goose bumps on the skin. Cognitive responses include recognition, emotion and learning. External responses include utterances or other communication, physical actions such as a slap in the face or an embrace, or avoidance of an obstacle. Keywords: objective local potential kinesthesia expression stimulus emotion laughter reflex instinctive References: cognition comprehension context perception
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Rete algorithm

Rete is latin for net, and it is an algorithm that breaks rules down into left and right sides and treats them as nodes in a network. The following explanation was borrowed from http://www.jessrules.com/docs/71/rete.html "The typical rule-based program has a fixed set of rules while the working memory changes continuously. However, it is an empirical fact that, in most rule-based programs, much of the working memory is also fairly fixed from one rule operation to the next. Athough new facts arrive and old ones are removed at all times, the percentage of facts that change per unit time is generally fairly small. For this reason, the obvious implementation for the rule engine is very inefficient. This obvious implementation would be to keep a list of the rules and continuously cycle through the list, checking each one's left-hand-side (LHS) against the working memory and executing the right-hand-side (RHS) of any rules that apply. This is inefficient because most of the tests made on each cycle will have the same results as on the previous iteration. However, since the working memory is stable, most of the tests will be repeated. You might call this the rules finding facts approach and its computational complexity is of the order of O(RF^P), where R is the number of rules, P is the average number of patterns per rule LHS, and F is the number of facts on the working memory. This escalates dramatically as the number of patterns per rule increases." "The Rete algorithm is implemented by building a network of nodes, each of which represents one or more tests found on a rule LHS. Facts that are being added to or removed from the working memory are processed by this network of nodes. At the bottom of the network are nodes representing individual rules. When a set of facts filters all the way down to the bottom of the network, it has passed all the tests on the LHS of a particular rule and this set becomes an activation. The associated rule may have its RHS executed (fired) if the activation is not invalidated first by the removal of one or more facts from its activation set." "Within the network itself there are broadly two kinds of nodes: one-input and two-input nodes. One-input nodes perform tests on individual facts, while two-input nodes perform tests across facts and perform the grouping function. Subtypes of these two classes of node are also used and there are also auxiliary types such as the terminal nodes mentioned above." [Forgy 1982]
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RISC

Reduced Instruction Set Computer is an attempt to design chips with simpler instruction sets so they can achieve greater cycle speeds. It was thought through the late 1980s and early 1990s that RISC might replace CISC chips as the brains of most computers. As of this writing, the RISC and CISC models coexist. In some future world, at the end of code as we know it, the instruction set may shrink further... Keywords: CISC architecture References: computing
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RNA

Ribonucleic acid. This is another helical structure in cells that helps make things. Acting as a messenger, RNA gets template information from DNA and carries it to ribosomes where new proteins are made to order. Keywords: DNA genetics References: brain physiology neurons neuroscience
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robot

A mechanical device that performs actions involving motion. Common robotic actions include moving the robot autonomously or walking; grasping, lifting and moving objects; welding and other skilled activities; and other manipulations of objects too precise or heavy for humans. Keywords: robotics AI ALife MIPUS android cerebellum References: AI programming cybernetics ethics genetics neural networks science fiction
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robotics

A machine science that designs machines to perform actions normally done manually. As the Latin root of manual (it means hand) suggests, arms and hands are a big part of the effort. Teaching a robot to pick up and hold a cup of liquid and locomote without spilling it is a monumental task. Keywords: AI ALife MIPUS android robot References: AI programming cybernetics ethics genetics neural networks science fiction
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robust

Strong, vigorous, well built or sturdy. In computational performance, a machine or an algorithm is considered robust if it is able to transcend and perform despite difficulties that would crash simpler or less flexible machines or algorithms. Fault tolerance is often equated with robustness. Keywords: algorithm process References: algorithms automata computing formalisms logic rules
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rule

A proposition that can be used to make an inference. In an expert system, the rules are said to fire when the system compares the facts (input) to the known behavior of facts in the domain of the expert system. Keywords: production system ATN proposition linguistics interaction equation data type fact exception rule base expert system inference domain input behavior References: algorithms automata computing expert systems formalisms logic rules
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rule base

A set of logical formulae describing real world relationships or functions that is used by an artificial intelligence program such as an expert system for performing inferences. Each rule in a rule base is a logical proposition, although the form of the rule may be any of a number of popular formats. Keywords: rule proposition model base fact decision support system inference knowledge base expert system knowledge References: algorithms automata computing expert systems formalisms logic rules
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sample space

In probability theory, the sample space is the universe of discourse. All possible outcomes of a scalar or nominal measurement constitute the sample space. Without probing too deeply into the formulae associated with determining probability, we can safely say that the distribution of cases in the sample space provides a basis for prediction. Keywords: search probability range constraint domain state space References: context inference information/entropy knowledge knowledge representation memory modeling pattern recognition probability
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schemata

The plural of scheme. In NeuroPedia we look at conceptual schemata as a form of knowledge representation. Conceptual schemata are like complex semantic networks. There are also many other knowledge representation schemes. Keywords: knowledge representation knowledge computing structure heuristic algorithm memory References: AI programming algorithms automata computing formalisms logic rules
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Schwann cell

A type of glial cell (neuroglia) that acts like a filled crepe. Its flat, pancake-like processes wrap around axons in the peripheral nervous system to insulate the axon membrane from outside electrical potentials. Thus, you may think of the axon as the cream or fruit filling of a French pastry. Keywords: neurogliaform myelin astrocyte axon neuroglia oligodendrocyte action potential References: brain physiology neurons neuroscience
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search

In computational systems, search is the way to find something in memory. The quality of the search technique governs the efficiency of the process and the reliability of the outcome. Keywords: hypertext sample space genetic algorithms state space References: AI programming algorithms automata computing formalisms logic rules
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segmentation

In continuous speech, the process of distinguishing the beginnings and ends of words. When we hear speech in an unfamiliar language, it may seem unnaturally rapid, so it is difficult for us to make out words. It usually takes a fair amount of experience and practice to develop a facility for hearing a foreign language. Keywords: word language learning interpretation References: lexicography linguistic strata natural language semantics syntax words/morphology
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self

An abstract concept in which an object is aware of the properties it possesses. Humans have a sense of self. A human perceives the physical attributes she or he possesses through the senses including kinesthesia. The expression "I am tired" presumes that the person percieves a dynamic characteristic associated with self. The context of self occupying a position in time and space provides a basis of context on which to develop expectations that are necessary for complex cognitive activities. Keywords: consciousness sense object property cognition expectations context
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self-similarity

A principle of nature that applies down to the most minute level. Some self-similar phenomena, such as particles of vapor in a cloud and neurons in the brain, often appear chaotic to the naked eye or microscope. Deep inspection reveals patterns and functional similarities that yield profound order. Keywords: continuum chaos fractal imagination creativity random References: chaos fuzzy logic logic modeling parallel computing physics probability
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semantic network

A knowledge representation scheme in which objects or concepts are stored as nodes or vertices in a graph and linked together with labeled relations such as "is_a" and "has_a" (e.g. DOG is_a ANIMAL / DOG has_a TAIL where DOG is a node with two links to other nodes). Keywords: link conceptual graph knowledge representation symbolic logic frame association References: comprehension information/entropy lexicography linguistic strata natural language semantics
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semantic tagging

The process of associating meaningful language markers with digitally stored and delivered information. Championed for the World Wide Web, semantic tagging was initially inline with the text, so each tag could be embedded in the HTML at the beginning of a document or with the text to which the tag applied. This is "tight coupling" because they are inextricably connected and to edit the tags, you have to edit the entire document, and possibly redeploy it. Metadata in DatabaseThen came Search Engine Optimization (SEO) in which the tools provide tagging which is separate from the document but still bound to the page using tools such as PHP or derivatives WordPress or Drupal. Finally, the loosely coupled strategy of using ontologies to perform the tagging made it possible to have completely separate processes for managing metadata and managing the content. This is especially valuable for tagging material you want to leave as is, such as a Shakespeare play or the Bible, a recorded Boston Pops concert, or a digital image of an impressionist painting or MRI of your heart. The tag lives separately and points to the associated content using a URI or URL.
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semantics

Language StrataI define semantics from a business perspective as "technology formalisms that provide structured representations of meaning and context to add business value to automated processes" that formerly or currently require human interpretation to establish such connections. Other definitions include:
  1. The study of meaning and roles in words and sentences.
  2. Semantic constraints tell us what roles words can and cannot play. Some roles are AGENT, INSTRUMENT, OBJECT, and ACTION. To be an action, a word or phrase must be a verb. Agents and objects are nominal.
  3. An argument that relies on word meanings in isolation without capturing the broader context
Keywords References
sememe  comprehension
pragmatics  context
MT  information/entropy
syntax  linguistic strata
language  natural language
linguistics semantics
meaningful  syntax
expressiveness  words/morphology

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sememe

The smallest unit of meaning in a language. A sememe can be a word or part of a word. There may be rare cases when a phrase can constitute a sememe. The way you can tell it is a sememe is if it holds meaning alone, without needing other parts of a word or other words. Keywords: word natural language semantics lexical linguistics meaningful expressiveness References: comprehension context information/entropy linguistic strata natural language semantics syntax words/morphology
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sense

1) One of the five human faculties of perception: sight, hearing, touch, taste, smell. These provide input to the cognitive aparatus. 2) To perceive. 3) To process input. Keywords: extra-sensory thalamus somatosensory cortex sentient olfactory integration filtering expectations diencephalon consciousness attention perception arousal cognition intelligence stimulus input cue kinesthesia sensory References: cognition comprehension context fuzzy logic inference knowledge logic perception
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sensory

Having to do with the senses. Keywords: image processing sentient sense perception arousal extra-sensory References: cognition comprehension context fuzzy logic inference knowledge logic perception
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sensory transduction

There are two main senses: 1) (From the UniProt knowledge base) Protein involved in sensory transduction, the process by which a cell converts an extracellular signal, such as light, taste, sound, touch or smell, into electric signals. 2) The process in which any cell converts the energy in a stimulus (such as propagated action potentials) into a change in the electrical potential across its membrane. Definition 2 may not technically be "sensory" transduction, but generic transduction. My suspicion is that there is no difference in the physical mechanism between receptor cells, which are associated with sensory stimuli, and all other neurons, which may be participating in more abstract cognitive functions largely independent (if that is possible) of immediate sensory input.
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sentence

A self-contained segment of language. Sentences are normally segregated from one another in text by some sort of punctuation and in speech by some sort of prosody (change in vocal intonation). A sentence is usually independently meaningful or can be understood to some extent even if it is taken out of context. Keywords: idiom word language grammar References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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sentient

A being or thing is described as sentient if it can feel or otherwise perceive, be aware or be conscious. A sentient computer would have to be able to perceive incoming sensory stimuli, be aware of the perception process, and perform conscious functions based on perceived stimuli. Keywords: sense sensory consciousness cue perception understanding References: AI programming computing cybernetics ethics expert systems genetics neural networks inference science fiction
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Service-Oriented Architecture

A systems design/architecture strategy with more separate, reusable programs designed as services, rather than fewer large applications. These smaller services are normally much simpler than large applications, with functionality limited to easily defined capabilities. The  services are often invoked through a service bus using a predefined mechanism governed by a contract. This is an important evolution in computing in that it brings us a step closer to the end of code that is independent of knowledge, and closer to knowledge-driven functionality (code).
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short-term memory

Also called working memory, short-term memory is where (or how) we store temporary representations of facts or objects for immediate processing. Whereas long-term recall requires either a profound or repeated exposure to the information, short-term memory can be fed by light rehearsal. In the metaphor of the mechanical brain, short-term memory would be the RAM. Keywords: recall episodic memory declarative memory procedural memory knowledge memory RAM References: associationism cognition inference knowledge learning memory taxonomy
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SIMD

Single Instruction, Multiple Data is a parallel processing architectural standard with multiple, often hundreds or thousands, of processors performing the same operations at the same time. The results of these parallel computations are later assembled to determine a result. Keywords: MIMD parallel computing computing granularity References: computing
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slicing and dicing

  1. Report DashboardA process often used in kitchens involving knives or small electric appliances to reduce the size of edibles
  2. A process used in Business Intelligence (BI) and analytics to change the view, add or remove details, or rearrange the data to make it easier for humans to analyze. Sometimes considered synonymous with filtering and sorting.

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software

This blog describes two kinds of software: 1) computer software that is the code that tells the hardware what to do with electrical impulses flowing in computers, and 2) cognitive software that is the learned patterns of impulse flow in the brain that enable us to think or process information. The distinction between brain hardware and cognitive software may be incorrect or irrelevant. The term cognitive software, however, serves us as we attempt to imitate thought. Keywords: program computer cognition brain modeling process information impulse References: AI programming algorithms automata computing
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soma

The cell body of a neuron. Not to be confused with the nucleus: the nucleus and other neural components are within the soma. Axosomatic synapses connect axons of other neurons directly to the soma, but the majority of electrical connections are made between axons and dendrites. Keywords: neuron axon dendrite cytoplasm References: brain physiology neurons neuroscience
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somatosensory cortex

Several areas of the cerebrum responsible for interpreting tactile stimuli. The Primary Somesthetic Cortex is Brodmann's areas 1-3. The Secondary is part of area 40. The Somesthetic Association Cortex covers areas 5 and 7. If the association cortex is injured, tactile agnosia or astereognosis can result. Keywords: perception sense association context tactile agnosia References: brain physiology neurons neuroscience
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space

Space can mean many things. Since we talk about universal theories in UnderstandingContext.com, we must define our perspective of space. From an information perspective, space refers primarily to the exact position in the universe in which the perceived or conceived action occurs, or the position of the person thinking about it. It is part of the dynamic duo of space and time, serving as a primary component of context. Keywords: context time information cognition domain References: context physics
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SPARQL

You want to get specific data in and out of RDF? You want to sparkle! If you dislike acronyms, here's one to make a patient person squirm. It's recursive: SPARQL Protocol and RDF Query Language. SPARQL was made a standard by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium (W3C), and is recognized as one of the key technologies of the semantic web. Similar to the way Structured Query Language (SQL or sequel) is used to get specific data in and out of relational databases, SPARQL is used for RDF data, often stored as "subject-predicate-object" triples in Graph Databases. Semantics
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specialization

A process of performing or learning to perform unique tasks or functions. The term is sometimes applied to things normally dedicated to a certain task but capable of generalized behavior. Specialization tends to suggest that the organization of neurons in the brain is more complex than can be easily modeled with perceptron or connectionist models where every node is functionally identical. Keywords: Brodmann cognition brain circuitry learning References: brain physiology neurons neuroscience
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spike

In neuroscience, a 3-5 millisecond burst of action potential across a synapse that can excite a neuron. If the spike is intense, it will force the electrical potential inside the cell to exceed a threshold and fire or propagate the impulse to other cells. Some action potentials last longer or decay more slowly. Keywords: exocytosis asymptote anticholinesterase action potential threshold firing synapse decay References: brain physiology neurons neuroscience
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spinal cord

A biological cable traversing the spinal column that serves as a link between the brain and the rest of the body. It is also a low-level integrating center for motor and sensory processing (for example it handles reflexes) while higher-level processes are handled in the brain. Keywords: nerve fiber peripheral nervous system brain integration perception brain stem reflex References: brain physiology neurons neuroscience
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SQL (Structured Query Language)

SQL (pronounced like the word "sequel") is a language used to access data in tables in a relational database management system (RDBMS). The language used a regular grammar and a set of reserved words to provide SQL developers the ability to create, read ("select"), update, append and delete data described within tables, and between tables linked by primary and foreign keys. The keys define the "relations" in "Relational".
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standard deviation

Standard deviation is a formula for measuring the distance from the center of the average result. It is the most commonly used indicator of degree of dispersion and is the most reliable measure for estimating the variability in a population. Standard deviation can be extremely useful in the context of discriminating between normal, exceptional and anomalous cases. The formula for standard deviation is the square root of the mean of the squared deviations from the mean of the distribution. Keywords: exception range statistical analysis probability References: algorithms automata computing logic rules
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state space

State space is similar to search space except that while the search space describes all possible solutions the search can find, the state space describes all possible states the system can enter between the beginning and end of processing. An ATN, for example, uses transitions within a set of states to perform all processes. Keywords: ATN algorithm sample space search References: algorithms automata computing formalisms logic
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statistical analysis

A process of assembling results and applying various mathematical formulae to analyze characteristics and patterns in the results. Stochastic techniques and probability theory provide tools for statistical analysis, as do the standard methods of calculating mean, median, average and standard deviation. The results of statistical analyses can often be depicted graphically, making them more meaningful. Keywords: stochastic probability analysis understanding inference standard deviation range References: algorithms automata computing formalisms logic rules
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stellate cells

A garden variety of smaller neurons found in the higher layers of the cerebrum and cerebellum. Their relatively symmetrical shape with nerve processes radiating within close proximity to the cell body gives them their name. They are sometimes called small granule cells. Keywords: neurogliaform fusiform cells cerebrum cerebellum basket cells granule cells Golgi cells Purkinje References: brain physiology neurons neuroscience
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stimulus

Anything internal or external that produces some impact on one of the five physical senses. Internally generated stimuli are called kinesthesia while external stimuli are called sensory input. Keywords: local potential binding response reflex kinesthesia sense perception References: brain physiology neurons neuroscience perception
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stochastic

Stochastic reasoning is a technique of analyzing data that predicts results based on probability factors. Keywords: heuristic constraint analysis statistical analysis probability reasoning dead man's hand random References: chaos inference logic probability
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strata

Plural of stratum: In geology, layers of rocks. Looking at geological strata can tell you about the environment of the period during which a stratum was the surface of the planet. In language, stratification refers to parts or features of phrases or sentences that get deeper and deeper into the meaning of the words. Keywords: language knowledge abstraction interpretation understanding grammar References: lexicography linguistic strata natural language semantics syntax words/morphology
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string

  1. Cat and StringA theory about how the universe works (see String Theory or Super String Theory)
  2. Something the cat likes to play with
  3. A sequence of symbols that are intended to represent meaning in one dimension
Parsing text strings of human language words is one of the initial processes in automated language understanding. Parsing
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structure

How a thing is put together. Structure in language is called syntax, in construction and computer hardware it is called architecture, in software it includes modularity and flow, and in cognition it involves seemingly chaotic patterns of association or connection. Understanding structure is half the battle when developing simulations such as AI. Keywords: symmetry taxonomy syntax schemata form pattern function References: associationism automata brain physiology chaos connectionism formalisms modeling physics syntax system engineering taxonomy
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subconscious

Something beneath or beyond consciousness: A chaotic admixture of emotions, judgements, perceptions and preconceived ideas that flavor cognitive activities, reasoning, thoughts, responses and interpretations that never bubble up to the point of  a person knowing or acknowledging that they are part of the outcome. If consciousness is a phenomenon of the mind, then subconscious activity may be the undergirding of the bridge that ties the mind and the brain together.
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subjective

An adjective describing a viewpoint or decision based on personal, emotional, or other non-scientific or less-than-logical criteria. Subjectivity is the hallmark of all human interaction and cognition. Keywords: objective amygdala emotion cognition logic References: cognition comprehension context ethics fuzzy logic inference information/entropy intelligence philosophy probability
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subliminal

Pre-consciously, loads of cognitive activity occurs, enabling humans to navigate the treacherous world of humans.
adjective Psychology
existing or operating below the threshold of consciousness; being or employing stimuli insufficiently intense to produce a discrete sensation but often being or designed to be intense enough to influence the mental processes or the behavior of the individual: a subliminal stimulus; subliminal advertising.

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sulcus

The sulci are the valleys dividing the folds of the gray matter or cortex. The deepest of the sulci are called fissures. They serve to segregate different areas of the cortex that perform different functions. Keywords: gyrus cortex gray matter References: brain physiology neurons neuroscience
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survival

In life (and artificial life) survival is a function of fitness. If an organism is to survive, it must deter or overcome forces that would terminate its life. In animals this is instinctive. In machines, this must be taught, though how to teach a machine to survive remains a mystery. Keywords: ALife AI genetics genetic algorithms References: Goldberg, 1989 Holland, 1975 algorithms genetics computing
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syllogism

A logical formula with premises followed by a conclusion: IF a AND b, THEN c. Conjunctions (AND) or disjunctions (OR) can be used to express the necessity of each of the premises. Keywords: logical form reasoning References: formalisms fuzzy logic knowledge representation logic philosophy
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symbol

A concrete or abstract thing used to represent another thing. Language is a symbolic process of using words (vocal or written symbols) to represent things or ideas. Barcodes and QR codes are visual symbols that are scannable by Symbol scanners. Computers are symbol manipulation systems based on two symbols, 1 and 0, representing opposites in a binary system of digital logic. Keywords: representation parsing node discriminate language process cognition modeling References: algorithms automata computing formalisms knowledge representation logic words/morphology
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symbolic logic

When logical expressions with pre-established meanings that overcome ambiguities inherent in natural languages are used in computing, it is called symbolic logic. Keywords: semantic network representation knowledge representation conceptual graph data processing computing inference References: cognition comprehension computing context fuzzy logic inference knowledge logic perception
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symmetry

Invariance against change. We often think of mirror symmetry when we hear this word, but it embodies more than just exact repetition. Symmetry can be achieved with similarity and minor differences. Creativity and innovation are often exercises in symmetry in which a variation on a theme is introduced that makes all the difference. Keywords: chaos form structure References: chaos formalism
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synapse

A point of linkage between two neurons. Nerve fibers act like wires conducting electricity. Synapses act like spark plugs: they have a little gap where electrical potential can be generated by chemical reactions from one side (axon) and propagated to the other side. Keywords: weight spike norepinephrine neurotransmitter link endocytosis decay channel brain circuitry anticholinesterase activation acetylcholine neuron axon dendrite action potential synaptic vesicle References: brain physiology neurons neuroscience
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synaptic vesicle

An organelle in neurons that is a spherical container for neurotransmitter chemicals. These are synthesized in the soma and transferred by microtubules to the synapses where they can discharge their contents across the membranes into the synaptic cleft where they can affect the flow of E/I impulses. Keywords: organelle neurotransmitter microtubules synapse E/I References: brain physiology neurons neuroscience
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syncretism

Syncretism is, in philosophy, the attempt to reconcile or join different or opposing principles, practices, or parties, as in philosophy or religion. In grammar, syncretism is merging two or more categories in a specified environment into one.   It "suggests that the mind keeps separate accounts for the templates that build words (for example "word = stem + suffix"), for scraps of sound that may be added to words (-s, -ed and -ing), and for the roles these additins can play" (Pinker 1999). grammar morphology
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synecdoche

All HandsSynecdoche is a form of speech in which you use a part to refer to its whole or vice-versa. Here are some good examples from World Wide Words: "You use this when you speak of a part of something but mean the whole thing. When Patrick O’Brian has Captain Jack Aubrey tell his first lieutenant to “let the hands go to dinner” he’s employing synecdoche, because he’s using a part (the hand) for the whole man. You can also reverse the whole and the part, so using a word for something when you only mean part of it. This often comes up in sport: a commentator might say that “The West Indies has lost to England” when he means that the West Indian team has lost to the English one. America is often used as synecdoche in this second sense, as the word refers to the whole continent but is frequently applied to a part of it, the USA." Synecdoche  is narrower than metonymy, which may use an individual or an attribute to describe an object, group or class. Metonymy and synecdoche both twist context in ways that only the broader context of the surrounding language can help a person (or machine) discern the true intent of the speaker or writer. metonymy  
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syntax

Language structure. The rules of structuring either natural (human) or synthetic (i.e. computer) languages are also called grammar rules. By understanding a language's syntax, we can learn its diction and presumably understand all well-formed statements or sentences in the language. (Not to be confused with its homonym, "sin tax", which is a type of luxury tax for things considered to be morally ambiguous) Keywords: semantics pragmatics MT morphology linguistics grammar form structure References: comprehension context information/entropy intelligence learning lexicography linguistic strata natural language semantics syntax words/morphology
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synthesis

To build or assemble. Think of synthesis in both a physical and an abstract way. Before the structure can be erected, the blueprint must exist. Synthesis of the blueprint, and before that, the concept, are critical factors. Cybernetics is, by definition, synthetic. Keywords: analysis References: algorithms automata comprehension formalisms fuzzy logic inference knowledge learning rules
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systaltic array

Systaltic Flow in ComputersA systaltic array is a connected set of computational nodes that support bi-directional (systolic and diastolic) information flow. Neural networks are one-directional models for processing and sometimes the opposite (backpropagation) for learning. As shown in the illustration at right, a systaltic process model may use process flow scripts or forward chaining inference in parallel with independent knowledge search and retrieval to solve complex problems.
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systaltic array

Son of systolic array, the systaltic array is a parallel computing architecture optimized for a two-way data flow. Keywords: systolic array parallel computing References: algorithms automata computing formalisms parallel computing
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systolic array

A parallel computer architecture and paradigm. Systolic parallel algorithms exhibit a directional flow such that data is divided and queued to go through the same sequence of processes moving from one processor to the next. The blood-flow metaphor bespeaks the flow of data through processors. Keywords: parallel computing systaltic array MIMD References: algorithms automata computing formalisms parallel computing
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tactile agnosia

Decrease in acuity of the senses in general, usually resulting from a lesion in the somesthetic association cortex. Since this area is responsible for sensory integration, cognitive capabilities that require multiple senses are profoundly impaired. Astereognosis impairs spatial awareness of parts of the body. Keywords: somatosensory cortex association aphasia pathology integration References: brain physiology neurons neuroscience learning pathology psychology
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taxonomy

Universe Biotic Abiotic TaxonomyThe science of categorizing or classifying things hierarchically. Object-oriented programming techniques use inheritance from classes to subclasses to imitate the fundamentally taxonomical structure of information in the real world and in the mind. Taxonomies are a key component of generalization, a basic human cognitive activity. Keywords: hierarchical relations categorize class inheritance generalization structure cognition form References: associationism cognition inference knowledge
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telecosm

That subspace of cyber universe you can only get to by grid wire – that is, the international telecom grid. There are pockets of cyberspace that are not yet wired to the rest of the world. These are some companies' internal networks and individual computers that are not yet connected. But the telecosm is where it's at. The internet and world wide web are subsets of the telecosm, as were Compuserve, AOL, Prodigy, bulletin boards and other dial-in services back when this was originally in writing. Keywords: cyberspace cybernetics communication digital References: automata chaos cybernetics information/entropy knowledge
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thalamus

Thalamus ProfileThe thalamus is a small structure within the brain located just above the brain stem between the cerebral cortex and the midbrain and has extensive nerve connections to both. The main function of the thalamus is to relay motor and sensory signals to the cerebral cortex. It also regulates sleep, alertness and wakefulness (Dr Ananya Mandal, MD on News.medical.net)
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thalamus

The sensory integration center of the brain. Once considered part of the basal ganglia, the thalamus is now treated as part of the diencephalon. Its central location in the CNS gives it access to information from all the sensory areas and output to the cerebrum and to motor control centers. Keywords: limbic system hypothalamus hippocampus emotion amygdala sense integration diencephalon References: brain physiology neurons neuroscience
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theory

A guess based on generalization. Given a knowledge about some things and how they work, we can observe similarities and predict the structures and functions of similar things. These predictions are theories, and they serve as a basis for scientific inquiry and discovery. We can formally or informally build probabilistic models that can give us very well-supported theories before experimentation begins. Keywords: knowledge generalization prediction empiricism probability modeling References: automata chaos cybernetics ethics formalisms intelligence knowledge modeling philosophy physics
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think

Definition: To use the intellectual faculties for judging, making decisions, making inferences, drawing conclusions, or forming opinions, etc. To muse, meditate, reflect, recollect or weigh issues. An exhausting process for some. Keywords: thought meta-knowledge expectations concept cognition intelligence psychology References: cognition comprehension context fuzzy logic inference knowledge logic perception
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thought

The past tense of think. A fleeting snippet of cognitive activity that surfaced long enough to attract the attention of the intelligent being involved in voluntary or involuntary cogitation. Whether or not a machine is capable of thought is a semantic issue of artificial intelligence and ALife. Keywords: reasoning reason meta-knowledge intuition impulse existential conclusion conceptual concept think cognition intelligence mechanical brain References: cognition comprehension context fuzzy logic inference knowledge logic perception
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threshold

The level of electric action potential that must be reached to cause a neuron or node in an artificial system to fire or become activated as the result of a spike of excitatory action potential (depolarization). Threshold functions can be either square or sigmoidal. See textual references below. Keywords: weight spike resting potential node hyperpolarization firing asymptote anticholinesterase activation action potential depolarization E/I References: algorithms associationism chaos connectionism fuzzy logic learning neural networks pattern recognition
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time

The first member of the dynamic duo of time and space. Space (or location) and time are the two primary components of context in human cognition. Without the contexts of our current location and the time of day and time in the history of mankind, it would be more difficult to interpret the things we see and hear. Keywords: context space domain cognition References: context physics
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tools

Things that help you do something. One view of information and computational systems is that they are the most important part of any business. Poeple who possess this view are becoming extinct. People who understand that computers can provide good tools with which to conduct real business have a survival trait worth possessing. Keywords: computing computer android design program References: AI programming algorithms chaos computing cybernetics expert systems formalisms fuzzy logic inference knowledge representation modeling pattern recognition system engineering
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translation

1) The process of converting information encoded in one symbol set (language) to another. 2) A spiritual transformation in which the subject (human) physically dies and is resurrected "in the twinkling of an eye." Keywords: idiom expressiveness expression acquisition interpretation language natural language communication References: comprehension fuzzy logic lexicography linguistic strata natural language words/morphology
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uncertainty

In information theory, certainty is the degree that information is considered true, complete or accurate. Uncertainty rises from false or misleading data elements, incomplete data, or ambiguous context. Confidence is the human response to certainty, so some information models use confidence values. Keywords: meta-knowledge experiment empiricism concept information entropy confidence References: context fuzzy logic knowledge representation logic taxonomy
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understanding

Knowing empathy is the first sense of this word that comes to mind. This is a word that is often used to indicate knowledge with wisdom and somehow implies experience. It is one of the more noble terms for cognitive capacity. Keywords: strata statistical analysis sentient idiom discriminate discern knowledge comprehension References: associationism cognition inference knowledge taxonomy
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Unstructured Content

Unstructured data includes most documents, web pages, images and rich media such as audio and/or video content that require humans to fully and correctly interpret. Digital information or knowledge that is in more unpredictable formats (unstructured content) is usually more richly expressive and interesting than structured information in databases, but harder to find and interpret without an application or process that gives it structure. It turns out that, for some unknown reason, humans like information to play hard-to-get. Adding formal governance to the authoring and publishing process has been strangely dubbed as structured content: strange because the content that is the subject of the definition is "unstructured data". Go figure. Structured Content
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voice recognition

Speech WavesI recognize my wife's voice on the phone, but this is way different. This voice recognition is a misnomer for computationally recognizing words when spoken (voiced) into a microphone. Speech to text or STT may be a better expression for this conversion that translates sound waves into patterns that can be matched with words and phrases to tell a digital device what a person just said (i.e. "read your lips"). This is also completely different from language understanding, which begins with the words and tries to determine what prompted you to say something, or your intent (i.e. "read your mind").
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volition

I define volition as the application of human cognition to action: you decide, you act - your volition is behind what you did. agent cognition decide action actionable
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weight

In most of the places where the word "weight" appears in the Understanding Context blog, it refers to the abstract concept of level of confidence or trust, or the amount of activation that spreads from one neuron to another in the brain, or from one node to another in an artificial neural network. When the aggregate weights coming into a node (or neuron) reach or exceed the threshold, action potential is further propagated. Keywords: node neurode neural network action potential E/I threshold synapse References: algorithms associationism connectionism fuzzy logic learning neural networks pattern recognition
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Wernicke's area

The receptive speech area. This is where knowledge of language is used to interpret or remember linguistic information. When this part of the brain is injured, a person's ability to interpret or remember things heard or read is impaired. The related disability is called aphasia. Keywords: natural language association Broca's area aphasia References: brain physiology neurons neuroscience
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white matter

Parts of the brain inside gray matter that are filled with nerve axons. The white color comes from the myelin sheaths (made of glial cells) that insulate the axons. Keywords: neurogliaform gray matter myelin neuroglia References: brain physiology neurons neuroscience
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word

1) A single lexical element in a language (look up a word in a dictionary). The process of segmentation is used in continuous speech analysis (listening) to distinguish the beginning and ending of words in text. 2) More than one word (i.e. a WORD from our sponsor). 3) The number of bits in a register in a computing mechanism (i.e. 32-bit word). 4) The Christian gospel... Keywords: sememe pragmatics idiom anaphora sentence morphology grammar segmentation lexical ambiguity References: chaos comprehension fuzzy logic lexicography linguistic strata natural language words/morphology
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workflow

A sequential model of a business process that may branch based on processes performed at each step in the workflow. Form SearchCIO: "Workflow is a term used to describe the tasks, procedural steps, organizations or people involved, required input and output information, and tools needed for each step in a business process." The key differentiator between true workflow modeling and rules modeling is the sequence. Workflow Linearity
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Yorrick

Yorrick as FetusYorrick is the name of a fictional human being I have invented to illustrate the knowledge acquisition and language acquisition processes. See the following posts: Yorrick: Seeds of Knowledge Remember Yorrick Conceptual Paradigms From Concept to Communication Knowing About Agents and Instruments
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zygote

One of the two cells (female egg cell and male sperm cell) that, together, form the basis of human fetal development. The DNA in each of these cells contains half of the information necessary to form a whole person. Keywords: DNA information References: genetics
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