ai-lect7 - Knowledge and reasoning second part Knowledge...

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1 Knowledge and reasoning – second part Knowledge representation Logic and representation Propositional (Boolean) logic Normal forms Inference in propositional logic Wumpus world example
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2 Knowledge-Based Agent Agent that uses  prior  or  acquired   knowledge to achieve its goals Can make more efficient decisions Can make informed decisions Knowledge Base (KB): contains a set of  representations  of facts about the  Agent’s environment Each representation is called a  sentence  Use some  knowledge representation  language , to TELL it what to know e.g.,  (temperature 72F) ASK agent to query what to do Agent can use inference to deduce new  facts from TELLed facts Knowledge Base Inference engine Domain independent algorithms Domain specific content TELL ASK
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3 Generic knowledge-based agent 1. TELL KB what was perceived Uses a KRL to insert new sentences, representations of facts, into KB 2. ASK KB what to do. Uses logical reasoning to examine actions and select best.
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4 Wumpus world example
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5 Wumpus world characterization Deterministic? Accessible? Static? Discrete? Episodic?
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Wumpus world characterization Deterministic? Yes – outcome exactly specified. Accessible? No – only local perception. Static? Yes – Wumpus and pits do not move. Discrete?
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This note was uploaded on 01/20/2011 for the course CS 6810 taught by Professor Hecker during the Spring '10 term at CSU East Bay.

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ai-lect7 - Knowledge and reasoning second part Knowledge...

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