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Computing & Information Sciences Kansas State University Wednesday. 26 Sep 2007 CIS 530 / 730: Artificial Intelligence Lecture 15 of 42 Wednesday, 27 September 2007 William H. Hsu Department of Computing and Information Sciences, KSU KSOL course page: http://snipurl.com/v9v3 Course web site: http://www.kddresearch.org/Courses/Fall-2007/CIS730 Instructor home page: http://www.cis.ksu.edu/~bhsu Reading for Next Class: Section 9.5 – 9.6, p. 295 - 310, Russell & Norvig 2 nd edition First-Order Logic: Resolution Discussion: AI Applications 2 of 3

Lecture 15 of 42

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Lecture 15 of 42. First-Order Logic: Resolution Discussion: AI Applications 2 of 3. Wednesday, 27 September 2007 William H. Hsu Department of Computing and Information Sciences, KSU KSOL course page: http://snipurl.com/v9v3 - PowerPoint PPT Presentation

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Page 1: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Lecture 15 of 42

Wednesday, 27 September 2007

William H. Hsu

Department of Computing and Information Sciences, KSU

KSOL course page: http://snipurl.com/v9v3

Course web site: http://www.kddresearch.org/Courses/Fall-2007/CIS730

Instructor home page: http://www.cis.ksu.edu/~bhsu

Reading for Next Class:

Section 9.5 – 9.6, p. 295 - 310, Russell & Norvig 2nd edition

First-Order Logic: ResolutionDiscussion: AI Applications 2 of 3

Page 2: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Lecture Outline

Reading for Next Class: Section 9.5 – 9.6, R&N 2e

Today Resolution theorem proving

Prolog as related to resolution

Decidability of SAT, VALID

Recursive, Recursive Enumerable, and Co-RE languages

MP4 & 5 preparations

Friday Logic programming in real life

Industrial-strength Prolog

Lead-in to MP4

Next Week

Page 3: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides byS. Russell, UC Berkeley

Logical Agents:Review

Page 4: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Example:Backward Chaining

Adapted from slides byS. Russell, UC Berkeley

Page 5: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Question: How Does This Relate to Proof by Refutation?

Answer Suppose ¬Query, For The Sake Of Contradiction (FTSOC)

Attempt to prove that KB ¬Query ⊢

Backward Chaining

Page 6: Lecture 15 of 42
Page 7: Lecture 15 of 42
Page 8: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Resolution Inference Rule

Adapted from slides byS. Russell, UC Berkeley

Page 9: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides by S. Russell, UC Berkeley

Conjunctive Normal (aka Clausal) Form:Conversion (Nilsson) and Mnemonic

Implications Out

Negations Out

Standardize Variables Apart

Existentials Out (Skolemize)

Universals Made Implicit

Distribute And Over Or (i.e., Disjunctions In)

Operators Out

Rename Variables

A Memonic for Star Trek: The Next Generation Fans

•Captain Picard:

•I’ll Notify Spock’s Eminent Underground Dissidents On Romulus

•I’ll Notify Sarek’s Eminent Underground Descendant On Romulus

Page 10: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides by S. Russell, UC Berkeley

Skolemization

Page 11: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides by S. Russell, UC Berkeley

Resolution Theorem Proving

Page 12: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides by S. Russell, UC Berkeley

Example:Resolution Proof

Page 13: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Offline Exercise:Read-and-Explain Pairs

Offline Exercise:Read-and-Explain Pairs

For Class Participation (PS5) With Your Assigned Partner(s)

Read: Chapter 10 R&N By 13 Oct 2007

Page 14: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides by S. Russell, UC Berkeley

Logic Programming vs. Imperative Programming

Page 15: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides by S. Russell, UC Berkeley

A Look Ahead:Logic Programming as Horn Clause

Resolution

Page 16: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Adapted from slides by S. Russell, UC Berkeley

A Look Ahead:Logic Programming (Prolog) Examples

Page 17: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Summary Points

From Propositional to First-Order Proofs Generalized Modus Ponens

Resolution

Unification Problem

Roles in Computer Science Type inference

Theorem proving

What do these have to do with each other?

Search Patterns Forward chaining

Backward chaining

Fan-in, fan-out

Page 18: Lecture 15 of 42

Computing & Information SciencesKansas State University

Wednesday. 26 Sep 2007CIS 530 / 730: Artificial Intelligence

Terminology

From Propositional to First-Order Proofs Generalized Modus Ponens

Resolution

Unification Problem

Most General Unifier (MGU)

Roles in Computer Science Type inference

Theorem proving

What do these have to do with each other?

Search Patterns Forward chaining

Backward chaining

Fan-in, fan-out