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CHAPTER 1:INTRODUCTION TO EXPERT SYSTEMS1

1.1 Introduction1

1.2 What Is an Expert System?1

1.3 Advantages of Expert Systems4

1.4 General Concepts of Expert Systems5

1.5 Characteristics of an Expert System8

1.6 The Development of Expert Systems Technology10

1.7 Expert Systems Applications and Domains15

1.8 Languages,Shells,and Tools21

1.9 Elements of an Expert System23

1.10 Production Systems28

1.11 Procedural Paradigms32

1.12 Nonprocedural Paradigms38

1.13 Artificial Neural Systems43

1.14 Connectionist Expert Systems and Inductive Learning49

1.15 Summary50

CHAPTER 2:THE REPRESENTATION OF KNOWLEDGE57

2.1 Introduction57

2.2 The Meaning of Knowledge57

2.3 Productions60

2.4 Semantic Nets63

2.5 Object-Attribute-Value Triples66

2.6 PROLOG and Semantic Nets67

2.7 Difficulties with Semantic Nets72

2.8 Schemata73

2.9 Frames74

2.10 Difficulties with Frames77

2.11 Logic and Sets78

2.12 Propositional Logic81

2.13 The First Order Predicate Logic86

2.14 The Universal Quantifier87

2.15 The Existential Quantifier88

2.16 Quantifiers and Sets90

2.17 Limitations of Predicate Logic91

2.18 Summary91

CHAPTER 3:METHODS OF INFERENCE97

3.1 Introduction97

3.2 Trees,Lattices,and Graphs97

3.3 State and Problem Spaces101

3.4 And-Or Trees and Goals106

3.5 Deductive Logic and Syllogisms109

3.6 Rules of Inference114

3.7 Limitations of Propositional Logic122

3.8 First Order Predicate Logic124

3.9 Logic Systems125

3.10 Resolution128

3.11 Resolution Systems and Deduction131

3.12 Shallow and Causal Reasoning133

3.13 Resolution and First Order Predicate Logic137

3.14 Forward and Backward Chaining143

3.16 Metaknowledge156

3.17 Summary157

4.1 Introduction165

4.2 Uncertainty165

CHAPTER 4:Reasoning Under Uncertainty165

4.3 Types of Error166

4.4 Errors and Induction168

4.5 Classical Probability169

4.6 Experimental and Subjective Probabilities173

4.7 Compound Probabilities175

4.8 Conditional Probabilities178

4.9 Hypothetical Reasoning and Backward Induction183

4.10 Temporal Reasoning and Markov Chains186

4.11 The Odds of Belief191

4.12 Sufficiency and Necessity193

4.13 Uncertainty in Inference Chains195

4.14 The Combination of Evidence200

4.15 Inference Nets207

4.16 The Propagation of Probabilities216

4.17 Summary220

CHAPTER 5:INEXACT REASONING227

5.1 Introduction227

5.2 Uncertainty and Rules227

5.3 Certainty Factors233

5.4 Dempster-Shafer Theory243

5.5 Approximate Reasoning256

5.6 The State of Uncertainty300

5.7 Summary301

CHAPTER 6:DESIGN OF EXPERT SYSTEMS309

6.1 Introduction309

6.2 Selecting the Appropriate Problem309

6.3 Stages in the Development of an Expert System311

6.4 Errors in Development Stages313

6.5 Software Engineering and Expert Systems315

6.6 The Expert System Life Cycle317

6.7 A Detailed Life Cycle Model320

6.8 Summary325

7.1 Introduction327

CHAPTER 7:INTRODUCTION TO CLIPS327

7.2 CLIPS328

7.3 Notation328

7.4 Fields330

7.5 Entering and Exiting CLIPS333

7.6 Facts334

7.7 Adding and Removing Facts337

7.8 Modifying and Duplicating Facts340

7.9 The Watch Command341

7.10 The Deffacts Construct342

7.11 The Components of a Rule344

7.12 The Agenda and Execution346

7.13 Commands for Manipulating Constructs350

7.14 The Printout Command353

7.15 Using Multiple Rules353

7.16 The Set-Break Command355

7.17 Loading and Saving Constructs357

7.18 Commenting Constructs358

7.19 Summary359

8.1 Introduction365

8.2 Variables365

CHAPTER 8:PATTERN MATCHING365

8.3 Multiple Use of Variables366

8.4 Fact Addresses367

8.5 Single-Field Wildcards370

8.6 Blocks World371

8.7 Multifield Wildcards and Variables376

8.8 Field Constraints382

8.9 Functions and Expressions385

8.10 Summing Values Using Rules389

8.11 The Bind Function391

8.12 I/O Functions392

8.13 Summary398

CHAPTER 9:ADVANCED PATTERN MATCHING405

9.1 Introduction405

9.2 The Game of Sticks405

9.3 Input Techniques405

9.4 Predicate Functions407

9.5 The Test Conditional Element407

9.6 The Predicate Field Constraint410

9.7 The Return Value Field Constraint411

9.8 The Sticks Program412

9.9 The OR Conditional Element413

9.10 The AND Conditional Element415

9.11 The NOT Conditional Element417

9.12 The EXISTS Conditional Element419

9.13 The FORALL Conditional Element422

9.14 The LOGICAL Conditional Element424

9.15 Utility Commands428

9.16 Summary430

CHAPTER 10:MODULAR DESIGN AND EXECUTION CONTROL437

10.1 Introduction437

10.2 Deftemplate Attributes437

10.3 Salience445

10.4 Phases and Control Facts448

10.5 Misuse of Salience453

10.6 The Defmodule Construct456

10.7 Importing and Exporting Facts459

10.8 Modules and Execution Control463

10.9 Summary471

CHAPTER 11:EFFICIENCY IN RULE-BASED LANGUAGES477

11.1 Introduction477

11.2 The Rete Pattern-Matching Algorithm477

11.3 The Pattern Network480

11.4 The Join Network483

11.5 The Importance of Pattern Order486

11.6 Ordering Patterns for Efficiency492

11.8 The Test CE and Efficiency493

11.7 Multifield Variables and Efficiency493

11.9 Built-In Pattern-Matching Constraints495

11.10 General Rules versus Specific Rules496

11.11 Procedural Functions498

11.12 Simple Rules versus Complex Rules500

11.13 Loading and Saving Facts503

11.14 Summary504

12.1 Introduction509

12.2 Certainty Factors509

CHAPTER 12:EXPERT SYSTEM DESIGN EXAMPLES509

12.3 Decision Trees513

12.4 Backward Chaining526

12.5 A Monitoring Problem538

12.6 Summary554

APPENDIX A:SOME USEFUL EQUIVALENCES557

APPENDIX B:SOME ELEMENTARY QUANTIERS AND THEIR MEANINGS559

APPENDIX C:SOME SET PROPERTIES561

APPENDIX D:CLIPS SUPPORT INFORMATION563

APPENDIX E:CLIPS COMMAND AND FUNCTION SUMMARY565

APPENDIX F:CLIPS BNF579

INDEX585