Inteligencia artificial en java

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Practical Artificial Intelligence
Programming With Java
Third Edition
Mark Watson
Copyright 2001-2008 Mark Watson. All rights reserved.
This work is licensed under a Creative Commons
Attribution-Noncommercial-No Derivative Works
Version 3.0 United States License.

November 11, 2008

Contents
Preface

xi

1 Introduction
1.1 Other JVM Languages . . . . . . . . . . . . . . . . . .. . . .
1.2 Why is a PDF Version of this Book Available Free on the Web? .
1.3 Book Software . . . . . . . . . . . . . . . . . . . . . . . . . .
1.4 Use of Java Generics and Native Types . . . . . . . . . . . . . .
1.5 Notes on Java Coding Styles Used in this Book . . . . . . . . .
1.6 Book Summary . . . . . . . . . . . . . . . . . . . . . . . . . .

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2 Search
2.1 Representation of Search State Space and Search Operators .
2.2 Finding Paths in Mazes . . . . . . . . . . . . . . . . . . . .
2.3 Finding Paths in Graphs . . . . . . . . . . . . . . . . . . . .
2.4 Adding Heuristics to Breadth First Search . . . . . . . . . .
2.5 Search and Game Playing . . . . . . . . . . . . . . . . . . .
2.5.1 Alpha-Beta Search . . . .. . . . . . . . . . . . . .
2.5.2 A Java Framework for Search and Game Playing . .
2.5.3 Tic-Tac-Toe Using the Alpha-Beta Search Algorithm
2.5.4 Chess Using the Alpha-Beta Search Algorithm . . .

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3 Reasoning
3.1 Logic . . . . . . . . . .. . . . . . . . . . .
3.1.1 History of Logic . . . . . . . . . . .
3.1.2 Examples of Different Logic Types .
3.2 PowerLoom Overview . . . . . . . . . . . .
3.3 Running PowerLoom Interactively . . . . . .
3.4 Using the PowerLoom APIs in Java Programs
3.5 Suggestions for Further Study . . . . . . . .

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4 Semantic Web
57
4.1 Relational Database Model Has Problems Dealing with Rapidly Changing Data Requirements . . . . . . . . . . . . . . . . . . . . . . . . 58
4.2 RDF: TheUniversal Data Format . . . . . . . . . . . . . . . . . . . 59
4.3 Extending RDF with RDF Schema . . . . . . . . . . . . . . . . . . 62
4.4 The SPARQL Query Language . . . . . . . . . . . . . . . . . . . . 63
4.5 Using Sesame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

iii

Contents
4.6
4.7
4.8

OWL: The Web Ontology Language . . . . . . . . . . . . . . . . .
KnowledgeRepresentation and REST . . . . . . . . . . . . . . . .
Material for Further Study . . . . . . . . . . . . . . . . . . . . . .

5 Expert Systems
5.1 Production Systems . . . . . . . . . . . . . . . . . . . .
5.2 The Drools Rules Language . . . . . . . . . . . . . . .
5.3 Using Drools in Java Applications . . . . . . . . . . . .
5.4 Example Drools Expert System: Blocks World . . . . .
5.4.1POJO Object Models for Blocks World Example
5.4.2 Drools Rules for Blocks World Example . . . . .
5.4.3 Java Code for Blocks World Example . . . . . .
5.5 Example Drools Expert System: Help Desk System . . .
5.5.1 Object Models for an Example Help Desk . . . .
5.5.2 Drools Rules for an Example Help Desk . . . . .
5.5.3 Java Code for an Example Help Desk . . . . . .
5.6 Notes on the Craft ofBuilding Expert Systems . . . . . .

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6 Genetic Algorithms
99
6.1 Theory . . . . . . . . . . . . . ....
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