专家系统原理与编程：英文版

PREFACE vii

CHAPTER 1: Introduction to Expert Systems 1

1.1 Introduction 1

1.2 What Is an Expert System 1

1.3 Advantages of Expert Systems 8

1.4 General Concepts of Expert Systems 9

1.5 Characteristics of an Expert System 12

1.6 The Development of Expert Systems Technology 14

1.7 Expert Systems Applications and Domains 20

1.8 Languages, Shells, and Tools 26

1.9 Elements of an Expert System 28

1.10 Production Systems 34

1.11 Procedural Paradigms 38

1.12 Nonprocedural Paradigms 45

1.13 Artificial Neural Systems 51

1.14 Connectionist Expert Systems and Inductive

Learning 58

1.15 The State of the Art in Artificial Intelligence 58

1.16 Summary 63

Problems 63

Bibliography 64

CHAPTER 2: The Representation of Knowledge 67

2.1 Introduction 67

2.2 The Meaning of Knowledge 69

2.3 Productions 74

2.4 Semantic Nets 78

2.5 Object-Attribute-Value Triples 82

2.6 PROLOG and Semantic Nets 83

2.7 Difficulties with Semantic Nets 88

2.8 Schemata 90

2.9 Frames 91

2.10 Difficulties with Frames 95

2.11 Logic and Sets 96

2.12 Propositional Logic 99

2.13 The First Order Predicate Logic 105

2.14 The Universal Quantifier 106

2.15 The Existential Quantifier 108

2.16 Quantifiers and Sets 109

2.17 Limitations of Predicate Logic 110

2.18 Summary 111

Problems 111

Bibliography 114

CHAPTER 3: Methods of Inference 115

3.1 Introduction 115

3.2 Trees, Lattices, and Graphs 116

3.3 State and Problem Spaces 120

3.4 AND-OR Trees and Goals 125

3.5 Deductive Logic and Syllogisms 129

3.6 Rules of Inference 136

3.7 Limitations of Propositional Logic 144

3.8 First-Order Predicate Logic 146

3.9 Logic Systems 148

3.10 Resolution 152

3.11 Resolution Systems and Deduction 154

3.12 Shallow and Causal Reasoning 157

3.13 Resolution and First-Order Predicate Logic 1(;1

3.14 Forward and Backward Chaining 167

3.15 Other Methods of Inference 173

3.16 Metaknowledge 182

3.17 Hidden Markov Models 183

3.18 Summary 184

Problems 185

Bibliography 188

CHAPTER 4: Reasoning under Uncertainty 189

4.1 Introduction 189

4.2 Uncertainty 190

4.3 Types of Error 192

4.4 Errors and Induction 194

4.5 Classical Probability 197

4.6 Experimental and Subjective Probabilities 202

4.7 Compound Probabilities 204

4.8 Conditional Probabilities 207

4.9 Hypothetical Reasoning and Backward Induction 212

4.10 Temporal Reasoning and Markov Chains 217

4.11 The Odds of Belief 222

4.12 Sufficiency and Necessity 224

4.13 Uncertainty in Inference Chains 227

4.14 The Combination of Evidence 232

4.15 Inference Nets 240

4.16 The Propagation of Probabilities 250

4.17 Summary 255

Problems 256

Bibliography 260

CHAPTER 5: Inexact Reasoning 261

5.1 Introduction 261

5.2 Uncertainty and Rules 262

5.3 Certainty Factors 268

5.4 Dempster-Shafer Theory 279

5.5 Approximate Reasoning 294

5.6 The State of Uncertainty 342

5.7 Some Commercial Applications of Fuzzy logic 344

5.8 Summary 346

Problems 346

Bibliography 350

CHAPTER 6: Design of Expert Systems 353

6.1 Introduction 353

6.2 Selecting the Appropriate Problem 354

6.3 Stages in the Development of an Expert System 358

6.4 Errors in Development Stages 362

6.5 Software Engineering and Expert Systems 367

6.6 The Expert System Life Cycle 370

6.7 A Detailed Life Cycle Model 373

6.8 Summary 379

Problems 380

Bibliography 380

CHAPTER 7: Introduction to CLIPS 383

7.1 introduction 383

7.2 CLIPS 384

7.3 Notation 385

7.4 Fields 387

7.5 Entering and Exiting CLIPS 390

7.6 Facts 392

7.7 Adding and Removing Facts 395

7.8 Modifying and Duplicating Facts 398

7.9 The Watch Command 399

7.10 The Deffacts ConstFuct 400

7.11 The Components of a Rule 401

7.12 The Agenda and Execution 404

7.13 Commands for Manipulating Constructs 408

7.14 The Printout Command 411

7.15 Using Multiple Rules 411

7.16 The Set-Break Command 413

7.17 Loading and Saving Constructs 415

7.18 Commenting Constructs 417

7.19 Variables 417

7.20 Multiple Use of Variables 419

7.21 Fact Addresses 420

7.22 Single-Field Wildcards 422

7.23 Blocks World 424

7.24 Multifield Wildcards and Variables 430

7.25 Summary 435

Problems 436

Bibliography 441

CHAPTER 8: Advanced Pattern Matching 443

8.1 Introduction 443

8.2 Field Constraints 443

8.3 Functions and Expressions 447

8.4 Summing Values Using Rules 451

8.5 The Bind Function 453

8.6 I/O Functions 454

8.7 The Game of Sticks 461

8.8 Predicate Functions 463

8.9 The Test Conditional Element 464

8.10 The Predicate Field Constraint 466

8.11 The Return Value Field Constraint 467

8.12 The Sticks Program 469

8.13 The OR Conditional Element 469

8.14 The AND Conditional Element 472

8.15 The NOT Conditional Element 473

8.16 The EXISTS Conditional Element 476

8.17 The FORAI_L Conditional Element 479

8.18 The LOGICAL Conditional Element 481

8.19 Summary 485

Problems 486

CHAPTER 9: Modular Design, Execution Control, and

Rule Efficiency 495

9.1 Introduction 495

9.2 Deftemplate Attributes 495

9.3 Salience 504

9.4 Phases and Control Facts 507

9.5 Misuse of Salience 512

9.6 The Defmodule Construct 514

9.7 Importing and Exporting Facts 518

9.8 Modules and Execution Control 522

9.9 The Rete Pattern-Matching Algorithm 530

9.10 The Pattern Network 533

9.11 The Join Network 536

9.12 The Importance of Pattern Order 539

9.13 Ordering Patterns for Efficiency 545

9.14 Multifield Variables and Efficiency 546

9.15 The Test CE and Efficiency 547

9.16 Built-In Pattern-Matching Constraints 549

9.17 General Rules versus Specific Rules 549

9.18 Simple Rules versus Complex Rules 551

9.19 Summary 554

Problems 555

Bibliography 562

CHAPTER 10: Procedural Programming 563

10.1 Introduction 563

10.2 Procedural Functions 563

10.3 The Deffunction Construct 571

10.4 The Defglobal Construct 582

10.5 The Defgenedc and Defmethod Constructs 590

10,6 Procedural Constructs and Defmodules 608

10.7 Useful Commands and Functions 610

10.8 Summary 617

Problems 618

CHAPTER 11: Classes, Instances, and Message-Handlers 623

11.1 Introduction 623

11.2 The Defclass Construct 623

11.3 Creating Instances 625

11.4 System-Defined Message-Handlers 626

11.5 The Definstances Construct 628

11.6 Classes and Inheritance 629

11.7 Object Pattern Matching 638

11.8 User-Defined Message-Handlers 650

11.9 Slot Access and Handler Creation 656

11.10 Before, After, and Around Messsage-Handlers 659

11.11 Instance Creation, Initialization, Handlers and Deletion Message-Handlers 677

11.12 Modifying and Duplicating Instances 680

11.13 Classes and Generic Functions 684

11.14 Instance Set Ouery Functions 685

11.15 Multiple Inheritance 690

11.16 Defclasses and Defmodules 697

11.17 Loading and Saving Instances 699

11.18 Summary 700

Problems 702

CHAPTER 12: Expert System Design Examples 705

12.1 Introduction 705

12.2 Certainty Factors 705

12.3 Decision Trees 710

12.4 Backward Chaining 724

12.5 A Monitoring Problem 736

12.6 Summary 755

Problems 756

Bibliography 757

APPENDIXES 759

APPENDIX A Some Useful Equivalences 759

APPENDIX B Some Elementary Quantifiers and

Their Meanings 760

APPENDIX C Some Set Properties 761

APPENDIX D CLIPS Support Information 762

APPENDIX E CLIPS Commands and Functions Summary 763

APPENDIX F CLIPS BNF 785

APPENDIX G Software Resources 793

index 827