'Function symbols' diaporamas de présentation

CSE 8389 Theorem Proving Peter-Michael Seidel

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Explorations in Artificial Intelligence

Explorations in Artificial Intelligence. Prof. Carla P. Gomes gomes@cs.cornell.edu Module 3 Logic Representations (Part 3). 3-First-order Logic. Pros and cons of propositional logic. ? Propositional logic is declarative

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Knowledge Representation using First-Order Logic

Knowledge Representation using First-Order Logic. Reading: Chapter 8, 9.1-9.2 First lecture slides read: 8.1-8.2 Second lecture slides read: 8.3-8.4 Third lecture slides read: Chapter 9.1-9.2 (lecture slides spread across two class sessions)

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Last time: Logic and Reasoning

Last time: Logic and Reasoning. Knowledge Base (KB): contains a set of sentences expressed using a knowledge representation language TELL: operator to add a sentence to the KB ASK: to query the KB Logics are KRLs where conclusions can be drawn Syntax Semantics

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Chapter 6

King Saud University College of Computer and Information Sciences Information Technology Department IT422 - Intelligent systems . Chapter 6. Knowledge Representation & Reasoning (part 2) First Order Logic. Introduction. Propositional logic pros:

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CS 9633 Machine Learning Learning Sets of Rules

CS 9633 Machine Learning Learning Sets of Rules. Two Major Types of Rules. Propositional Sunny ? Warm ? PlayTennis First order predicate logic Parent(x,y) ? Ancestor(x,y) Parent(x,y) ?Parent(y,z) ? Ancestor(x,z). Sequential Covering Algorithms.

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CASL-Common Algebraic Specification Language

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Automated reasoning and theorem proving

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Using Views to Implement Datalog Programs

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First-Order Logic Syntax

First-Order Logic Syntax. Reading: Chapter 8, 9.1-9.2, 9.5.1-9.5.5 FOL Syntax and Semantics read: 8.1-8.2 FOL Knowledge Engineering read: 8.3-8.5 FOL Inference read: Chapter 9.1-9.2, 9.5.1-9.5.5 (Please read lecture topic material before and after each lecture on that topic).

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Knowledge Representation using First-Order Logic

Knowledge Representation using First-Order Logic. Reading: Chapter 8, 9.1-9.2 First lecture slides read: 8.1-8.2 Second lecture slides read: 8.3-8.4 Third lecture slides read: Chapter 9.1-9.2 (lecture slides spread across two class sessions)

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Lectures 13-14 First-Order Logic

Lectures 13-14 First-Order Logic. CSE 573 Artificial Intelligence I Henry Kautz Fall 2001. Axiom Schemas. Useful to allow schemas that stand for sets of sentences. Blowup: (index range) nesting for i, j in {1, 2, 3, 4} such that adjacent(i,j): for c in {R, B, G}: ( ? Xc,i ? ? Xc,j).

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Equivalent Formalisms For Turing Machine

Equivalent Formalisms For Turing Machine. CS6800. By Tiba Zaki & Abdalrahman Alsaedi. Equivalent Formalisms.

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First-Order Logic Semantics

First-Order Logic Semantics. Reading: Chapter 8, 9.1-9.2, 9.5.1-9.5.5 FOL Syntax and Semantics read: 8.1-8.2 FOL Knowledge Engineering read: 8.3-8.5 FOL Inference read: Chapter 9.1-9.2, 9.5.1-9.5.5 (Please read lecture topic material before and after each lecture on that topic). Outline.

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Lecture 9b: Prolog

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First-Order Logic Semantics

First-Order Logic Semantics. Reading: Chapter 8, 9.1-9.2, 9.5.1-9.5.5 FOL Syntax and Semantics read: 8.1-8.2 FOL Knowledge Engineering read: 8.3-8.5 FOL Inference read: Chapter 9.1-9.2, 9.5.1-9.5.5 (Please read lecture topic material before and after each lecture on that topic). Outline.

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FIRST-ORDER LOGIC

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Reasoning with Infinite stable models

Reasoning with Infinite stable models. Piero A. Bonatti presented by Axel Polleres http://sansone.crema.unimi.it/~bonatti/pub/ijcai01.pdf (IJCAI 2001, full version to appear in AIJ). Finitary normal logic programs.

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