Category Archives: Computing
Computing hardware, parallel approaches to software and hardware design, automation
17 Oct Neural Conceptual Dependency
Conceptual Dependency Much of this blog has been about knowledge representation: how the brain might learn and process it, how cognitive functions treat knowledge, and now, how computers may store and process it. Conceptual structures and conceptual dependency theories for computation have been useful for categorizing and representing knowledge in intuitively simple and cognitively consistent […]
14 Oct Knowledge in Non-Neural Models
Non-Neural Models So far we have examined a number of models that are explicitly designed to be neuromorphic. This categorization is useful for two reasons: the apparent chaos or non-deterministic functioning of the brain is represented by these models; and neural networks explicitly use large numbers of distributed processors or neurodes that each contribute to […]
28 Aug Weight Control for Knowledge
Stochastic Models Data, information and knowledge may be stored in many different ways in computers. Most artificial neural models rely heavily on stochastic or probabilistic techniques for establishing the internal structure that represents the data. The generalized delta rule for adaptation is an example of this sort of technique. The generalized delta rule, developed by D.E. […]
08 Aug The Fourth Dimension
To everything, turn, turn, turn, there is a season… Time is a fundamental and omnipresent element of context. It goes intrinsically with space, so much so, that we sometimes hear about a “time-space continuum” in which all things occur. Space and time are relevant to brain processes: electrical potential moves through physical pathways and brain […]
28 Jul Patterns in the Mind
As we look for suitable solution designs for representing the knowledge and processes we humans use to communicate, we realize that we have no idea what knowledge in the brain looks like. Further, we only have relatively vague ideas about the processes that occur in the brain as we produce and comprehend words, phrases and sentences. […]
26 Jul Parallel Distributed Pattern Processing
PDP Networks We have discussed recognition processes in the brain. Connectionism, a fundamentally implicit approach to neural modeling, was championed by the parallel distributed processing (PDP) group. PDP networks use many interconnected processing elements (PEs) that, according to the PDP Group, configure themselves to match input data with “minimum conflict or discrepancy” (Rumelhart & McClelland, 1986, Vol. 2, […]
15 Jul From Perception and Learning to Logic
Perception and Learning I am not a cognitive scientist, so all I have said in this section is based on the work of others. On the other hand, I have probably spent more time seriously studying cognition than most computer geeks, and I have tried to form my perspectives around the best of our knowledge. The […]
07 Jul SPARQL Fireworks
How do you get at knowledge in conceptually structured information stores such as graphs? There are multiple ways to get data and information in broad use today. The most common is Structured Query Language (SQL) which is used as the almost universal access formalism for getting, storing and manipulating data in relational databases. An emerging standard […]
03 Jul Do Yawl do Petri Nets
Where do you draw a line? In geometry, digital theory, language and time, patterns tend to be linear: they bear distinct sequences. The sequences in these domains either contribute to the meaningfulness of the patterns, or, in the case of time, are the foundation of the patterns. Any logic that focuses on these sequential patterns is linear logic. Temporal Logic […]