Tag Archives: cognitive modeling
20 Nov Identifying and Acquiring Knowledge
One of the simplest knowledge systems is a photograph. It consists of a systematically arranged collection of pixels and its design is based almost completely on framing and focusing. Specifying knowledge software involves framing the knowledge domain and focusing on the aspects that are meaningful to users, and the constraints that affect meaning. By so saying, […]
17 Nov Environmental Awareness for AI Geeks
Selecting an Environment and Tools I plan to take a few posts in this section to focus on expert systems (Giarratano 1989), exploring the development process in greater detail. While some projects require no development, some require you to select a platform or development environment or both. There are specially designed development platforms, tools and environments that provide much of the […]
28 Oct Chemicals And Cognitive Performance
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 […]
21 Oct Fuzzy Interconnectedness
Fuzzy and Interconnected Techniques Section 5 suggests that the software of cognition is very fuzzy and able to operate efficiently even without having complete or totally accurate information. We said that we want to replicate that flexibility. We spoke in Section 7 about different fuzzy approaches for representing and processing information. These approaches include artificial […]
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 […]
08 Sep Gnostic Learning Model
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 […]
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. […]
25 Aug Determinacy in Neural Connections
For many years, researchers thought that it was wrong to assume that there was a cell or set of cells in the brain that stored the memory of Grandma’s face. Though the comparison with computer memory was appealing, it was thought to be too simplistic and incorrect. Now, more researchers in different academic disciplines are assuming […]