2.shultz_pg76-94;136-143

2.shultz_pg76-94;136-143 - Knowledge representation How is...

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Knowledge representation How is knowledge represented and what the processes are that operate on those representations Representation: rules and connections Rule –based cognition Knowledge can be represented in symbols and processed by performing manipulations to these symbols. Symbols refer to objects in world and can be grouped to form larger symbolic structures like propositions, which can create even larger structures like rules that can contain instructions on how to perform computations over symbols (symbols proposition rule) o i.e. if two rows equal … then same number of objects o rule is the whole thing, propositions are the individual if/then statements, symbols are the rest Production systems o Rules can implement any computational procedure (turing-equivalent). To produce new knowledge, rules are processed by software (production systems) o Made of: rules (long term memory for how to accomplish a procedure – if/then statements), facts (working memory propositions – what the system currently knows about the problem it is working on), interpreter (software that drives the system by interpreting rules and keeping track) o Matching-selecting-acting procedure: conditional parts (if) of rules matched with working memory to determine which rule needed for firing. Interpreter selects one or a few rules for firing. Different rule selection criteria can be used (order = first rule whose conditions match working memory; priority values can specify which rules more important etc.). Then, once rule fired, rule’s conclusions deposited as new facts in working memory and 3 phase cycle continues. Direction of reasoning: can be forward or backward (forward seen above – data driven or bottom up reasoning). Reasoning backwards starts with a goal (theory driven). Rule conclusions examined to find conclusions that match the main goal. Conditions of these rules then examined to see what would need to be true to enable the main conclusion and this leads to search for rules whose conclusions and these conditions. Both examples below are examples of this.
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This note was uploaded on 02/14/2011 for the course PSYC 532 taught by Professor Shultz during the Fall '10 term at McGill.

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2.shultz_pg76-94;136-143 - Knowledge representation How is...

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