kb-systems-2up - 1 Artificial Intelligence CS4365 ---...

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Unformatted text preview: 1 Artificial Intelligence CS4365 --- Spring 2009 a Knowledge Representation and Reasoning Reading: Chapters 7-9, R&N 2 The Wampus World A decision-maker needs to represent knowledge of the world and reason with it in order to safely explore this world. 3 The Blocks World 4 Knowledge Representation • Human intelligence relies on a lot of background knowledge (the more you know, the easier many tasks become / “knowledge is power” ) • E.g. SEND + MORE = MONEY puzzle. • Natural language understanding — Time flies like an arrow. — Fruit flies like bananas. — The spirit is willing but the flesh is weak. (English) — The vodka is good but the meat is rotten. (Russian) • Or: Plan a trip to L.A. 5 • Q. How did we encode (domain) knowledge so far? For search problems? Fine for limited amounts of knowledge / well-defined domains. Otherwise: knowledge-based systems approach . 6 Knowledge-Based Systems / Agents Key components: • knowledge base : a set of sentences expressed in some knowledge representation language • inference / reasoning mechanisms to query what is known and to derive new information or make decisions Natural candidate: logical language (propositional / first-order) combined with a logical inference mechanism How close to human thought? In any case, appears reasonable strategy for machines. 7 Logic as a Knowledge Representation Three components: syntax: specifies which sentences can be constructed in a given formal logic semantics: specifies what a sentence means proof theory: a set of general purpose rules that allow efficient derivation of new information from the sentences in the knowledge base To make it work, we need a sound and complete proof theory. 8 Connecting Sentences to the Real World 9 Tenuous Link to Real World All computer has are sentences (hopefully about the world). 10 KR Language: Propositional Logic Syntax: build sentences from atomic propositions, using connectives ∨ , ∧ , • • , g159 , ⇔ . (and / or / not / implies / equivalence (biconditional)) E.g.: (( • • P ) ∨ ( Q ∧ R )) g159 S 11 Semantics Semantics specifies what something means . In propositional logic, the semantics (i.e., meaning) of a sentence is the set of interpretations (i.e., truth assignments) in which the sentence evaluates to True. Example: The semantics of the sentence P ∨ Q g159 R is • P is true , Q is True , R is True • P is true , Q is False, R is True • P is False , Q is False , R is True • P is False , Q is False , R is True • P is False , Q is False , R is False 12 Interpretations: The Key to Semantics An interpretation is a logician’s word for “truth assignment”. Given 3 propositional symbols P , Q , R , there are 8 interpretations....
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This note was uploaded on 07/02/2009 for the course CS 4365 taught by Professor Vincent during the Spring '09 term at Universidad Torcuato Di Tella.

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kb-systems-2up - 1 Artificial Intelligence CS4365 ---...

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