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26 Nov Planning and Scheming

Paint a Brain

Select a Knowledge Representation (KR) Scheme In prior posts I have been describing the steps of building knowledge systems. A major part of Step 3: Task 1 is defining how to store knowledge – selecting a scheme. Giarratano and Riley (1989) suggest making the selection of a scheme, such as rules, frames or logic, dependent upon […]

02 Jun Framing Formal Logic

Fuzzy Brain

Formal Logic Formal logic often uses set theory. Set theory uses existential (an assertion that something applies to some members of a set) and universal (a statement that applies to all members in a set) quantifiers. Despite the utility and noncommittal correctness of existential quantifiers, set operations using existential quantifiers are weaker then those using universal quantifiers. The […]

30 May State of the Art in Knowledge Representation

Digital Data Stream

KR Evolves Slowly The state of the art in computer programming has evolved toward data-driven techniques. In early programs, the data was “hard-coded” into the program with specific functions operating differently on each data item and type. Gradually, programmers began storing data and templates in different files, attempting to write orthogonal procedures to introduce a modularity […]

04 Mar Gnosticism, Mysticism and Hard Knowledge


Neural Network science describes oft rejected explicit knowledge in neurons as “gnostic cells” or “gramma cells” suggesting one neuron knows about gramma. Not all scientists agree with associationist theories that explain learning in the context of things that pre-exist in memory. In fact, an entire school of thought flatly rejects explicit representations that form the core […]