Lecture 16-Logical Reasoning

Lecture 16-Logical - CS 561 Artificial Intelligence Instructor TAs Sofus A Macskassy [email protected] Nadeesha Ranashinghe([email protected] William

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CS 561: Artificial Intelligence Instructor: Sofus A. Macskassy, [email protected] TAs: Nadeesha Ranashinghe ( [email protected] ) William Yeoh ( [email protected] ) Harris Chiu ( [email protected] ) Lectures: MW 5:00-6:20pm, OHE 122 / DEN Office hours: By appointment Class page: http://www-rcf.usc.edu/~macskass/CS561-Spring2010/ This class will use http://www.uscden.net/ and class webpage - Up to date information - Lecture notes - Relevant dates, links, etc. Course material: [AIMA] Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig. (2nd ed)
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Logical reasoning systems (Ch 9/10) Theorem provers and logic programming languages Provers: use resolution to prove sentences in full FOL. Languages: use backward chaining on restricted set of FOL constructs. Production systems Based on implications, with consequents interpreted as action (e.g., insertion & deletion in KB). Based on forward chaining + conflict resolution if several possible actions. Frame systems and semantic networks Objects as nodes in a graph, nodes organized as taxonomy, links represent binary relations. Description logic systems Evolved from semantic nets. Reason with object classes & relations among them. 2 CS561 - Lecture 16 - Macskassy - Spring 2010
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Basic tasks Add a new fact to KB TELL Given KB and new fact, derive facts implied by conjunction of KB and new fact. In forward chaining: part of TELL Decide if query entailed by KB ASK Decide if query explicitly stored in KB restricted ASK Remove sentence from KB: distinguish between correcting false sentence, forgetting useless sentence, or updating KB re. change in the world. 3 CS561 - Lecture 16 - Macskassy - Spring 2010
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define syntax and map sentences onto machine representation. Compound: e.g., c = P(x) Q(x) Op[c] = ; Args[c] = [P(x), Q(x)] FETCH: find sentences in KB that have same structure as query. ASK makes multiple calls to FETCH. STORE: add each conjunct of sentence to KB. Used by TELL. e.g., implement KB as list of conjuncts TELL(KB, A   B) TELL(KB, C D) then KB contains: [A, B, C, D] 4 CS561 - Lecture 16 - Macskassy - Spring 2010
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Complexity With previous approach, FETCH takes O(n) time on n-element KB STORE takes O(n) time on n-element KB (if check for duplicates) Faster solution? 5 CS561 - Lecture 16 - Macskassy - Spring 2010
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Table-based indexing What are you indexing on? Predicates (relations/functions). Example: Key Positive Negative Conclusion Premise Mother Mother(ann,sam) Mother(grace,joe) -Mother(ann,al) xxxx xxxx dog dog(rover) dog(fido) -dog(alice) xxxx xxxx 6 CS561 - Lecture 16 - Macskassy - Spring 2010
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Table-based indexing Use hash table to avoid looping over entire KB for each TELL or FETCH e.g., if only allowed literals are single letters, use a 26-element array to store their values. More generally:
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This note was uploaded on 08/26/2010 for the course CSCI 561 taught by Professor Staff during the Spring '08 term at USC.

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Lecture 16-Logical - CS 561 Artificial Intelligence Instructor TAs Sofus A Macskassy [email protected] Nadeesha Ranashinghe([email protected] William

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