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04 Jul Cognitive Multi-Processing

Layered Model

Today I’ll address parallel computing and models for breaking down computational problems. I will not address the question of autonomy today, but save the question of empowering independent agents for a future post. ANS and Multiprocessors Artificial Neural Systems (ANS) are probably the closest approximation of the mechanical brain paradigm, so it is useful to know how […]

30 Nov Architecting Meaningful Relationships


How do you know — anything? Chemicals and electrical impulses splash around in the brain, and voila: we understand the meaning of life, the universe and everything. We have looked at how synapses connect neurons, and how taxonomical and other associations connect concepts, but is it even possible for a computer to understand the complex […]

23 Feb Inference in Knowledge Apps

Thinking Process

In Section 5 we discussed different kinds of knowledge, including existential or hierarchical knowledge and causal knowledge. In Section 7 we discussed modeling approaches and search techniques that could be applied to any kind of knowledge. We saw that causal knowledge can be modeled as chains of causes and effects, and that existential knowledge can be […]

28 Oct Chemicals And Cognitive Performance

Lightning Brain

Outside Influences Mind-altering chemicals, stimulants, depressants and hallucinogens to name a few, affect the entire process of cognition, from receiving and processing input, through recognition and reasoning. They often even improve or impair our ability to act, affecting everything from muscle performance to language production and comprehension. Bacteria and viruses can also impact people. Things that come from outside […]

27 Oct The Nature of Innovative Thinking

Mental Exploration The shape of the world changed radically when folks from the eastern and western hemispheres became aware of one another and of their respective geographies. The Age of Exploration (AKA the Age of Discovery) was amazing – or should I say “it is amazing”? While the focus has changed from continents and cultures, to galaxies […]

17 Oct Neural Conceptual Dependency

Representing Conceptual Graphs

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 […]

08 Sep Gnostic Learning Model

Hard Disk in Brain

In prior posts in this section, and periodically in other sections of my blog, I have been exploring how humans learn, and how we might replicate those processes in computer software or (less likely) hardware. The context of the learning, or knowledge acquisition, upon which I choose to focus is language learning. While knowledge acquisition is much broader, this is an […]

21 May Modeling After a Fashion

Robot Platoon

Perennial Image Problems Artificial Intelligence has an image problem. Yes, there are cybernetic characters like R2D2, C3P0 and Commander Data whom we love, but some products built using AI techniques have the dubious reputation of being useful but not entirely dependable. Think of songs sung about Sirius Cybernetics Teleporter products (see lyrics below). It is possible that […]

07 May Pairs of Language Strata

Domain Concept Symbol Idea

The Paired Model By pairing language strata, we attempt to find or describe symmetrical structures in language, thus helping clarify one of the most abstract phenomena known to man: verbal communication. This pairing of characteristics is also useful in decomposing the problem into smaller chunks to make it easier for computers to deal with. A note […]

06 May Impulse Waves in Layers


Layered Model Just as the brain has areas with three to six distinct layers, a typical artificial neural systems (ANS) also has several layers. The example at right shows a network with three layers that illustrate a neural network‘s distributed architecture. The uniform circles connected by lines are symbolic of the state of an ANS at […]