CONTENTS
Preface = xiii
FOREWORD TO THE FIRST EDITION = xvi
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 = 5
1.4 General Concepts Of Expert Systems = 6
1.5 Characteristics Of An Expert System = 9
1.6 The Development Of Expert Systems Technology = 11
1.7 Expert Systems Applications And Domains = 17
1.8 Languages, Shells, And Tools = 23
1.9 Elements Of An Expert System = 25
1.10 Production Systems = 31
1.11 Procedural Paradigms = 35
1.12 Nonprocedural Paradigms = 41
1.13 Artificial Neural Systems = 47
1.14 Connectionist Erxpert Systems And Inductive Learning = 54
1.15 Summary = 54
CHAPTER 2 THE REPRESENTATION OF KNOWLEDGE = 63
2.1 Introduction = 63
2.2 The Meaning Of Knowledge = 63
2.3 Productions = 66
2.4 semantic Nets = 69
2.5 Object-Attribute-Value Triples = 73
2.6 Prolog And Semantic Nets = 74
2.7 Difficulties With Semantic Nets = 79
2.8 Schemata = 80
2.9 Frames = 82
2.10 Difficulties With frames = 85
2.11 Logic And Sets = 86
2.12 Propositional Logic = 90
2.13 The First Order Predicate Logic = 95
2.14 The Universal Quantifier = 96
2.15 The Existential Quantifier = 98
2.16 Quantifiers And Sets = 99
2.17 LImitations Of Predicate Logic = 100
2.18 Summary = 101
CHAPTER 3 METHODS OF INFERENCE = 107
3.1 Introduction = 107
3.2 Trees, Lattices, And Graphs = 107
3.3 State And Problem Spaces = 111
3.4 And-Or Trees And Goals = 117
3.5 Deductive Logic And Syllogisms = 119
3.6 Rules Of Inference = 127
3.7 Limitations Of Propositional Logic = 135
3.8 First Order Predicate Logic = 137
3.9 Logic Systems = 139
3.10 Resolution = 142
3.11 Resolution Systems And Deduction = 146
3.12 Shallow And Causal Reasoning = 148
3.13 Resolution And First Order Predicate Logic = 152
3.14 Forward And Backward Chaining = 158
3.15 Other Methods Of Inference = 165
3.16 Metaknowledge = 173
3.17 Summary = 174
CHAPTER 4 REASONING UNDER UNCERTAINTY = 183
4.1 Introduction = 183
4.2 Uncertainty = 183
4.3 Types Of Errors = 184
4.4 Errors And Induction = 186
4.5 Classical Probability = 188
4.6 Experimental And Subjective Probabilities = 192
4.7 Compound Probabilities = 194
4.8 Conditional Probabilities = 197
4.9 Hypothetical Reasoning And Backward Induction = 203
4.10 Temporal Reasoning And Markov Chains = 207
4.11 The Odds Of Belief = 212
4.12 Sufficiency And Necessity = 214
4.13 Uncertainty In Inference Chains = 217
4.14 The Combination Of Evidence = 223
4.15 Inference Nets = 230
4.16 The Propagation Of Probabilities = 239
4.17 Summary = 243
CHAPTER 5 INEXACT REASONING = 251
5.1 Introduction = 251
5.2 Uncertainty And Rules = 251
5.3 Certainty Factors = 258
5.4 Dempster-Shafer Theory = 268
5.5 Approximate Reasoning = 283
5.6 The State Of Uncertainty = 332
5.7 Summary = 332
CHAPTER 6 THE DESIGN OF EXPERT SYSTEMS = 341
6.1 Introduction = 341
6.2 Selecting The Appropriate Problem = 341
6.3 Stages In The Development Of An Expert System = 343
6.4 Errors In Development Stages = 345
6.5 Software Engineering And Expert Systems = 346
6.6 The Expert System Life Cycle = 349
6.7 A Detailed Life Cycle Model = 353
6.8 Summary = 360
CHAPTER 7 INTRODUCTION TO CLIPS = 363
7.1 Introduction = 363
7.2 CLIPS = 363
7.3 Notation = 364
7.4 Fields = 366
7.5 Entering And Exiting CLIPS = 369
7.6 Facts = 371
7.7 Adding And Removing Facts = 374
7.8 Modifying And Duplicating facts = 377
7.9 The Watch Command = 378
7.10 The Deffacts Construct = 379
7.11 The components Of A Rule = 380
7.12 The Agenda And Execution = 383
7.13 Commands For Manipulating Constructs = 386
7.14 The Printout Command = 389
7.15 Using Multiple Rules = 390
7.16 The Set-Break Command = 392
7.17 Loading And Saving Constructs = 394
7.18 Commenting Constructs = 395
7.19 Summary = 396
CHAPTER 8 PATTERN MATCHING = 401
8.1 Introduction = 401
8.2 Variables = 401
8.3 Multiple Use Of Variables = 402
8.4 Fact Addresses = 403
8.5 Single-Field Wildcards = 406
8.6 Blocks World = 407
8.7 Multifield Wildcards And Variables = 413
8.8 Field Constraints = 418
8.9 Functions And Expressions = 422
8.10 Summing Values Using Rules = 426
8.11 The Bind Function = 428
8.12 I/O Functions = 429
8.13 Summary = 436
CHAPTER 9 ADVANCED PATTERN MATCHING = 441
9.1 Introduction = 441
9.2 the Game Of Sticks = 441
9.3 Input Techniques = 441
9.4 Predicate Functions = 443
9.5 The test Conditional Element = 444
9.6 The Predicate Field Constraint = 446
9.7 The Return Value Field Constraint = 447
9.8 The Sticks Program = 448
9.9 The Or Conditional Element = 449
9.10 The And Conditional Element = 452
9.11 The Not Conditional Element = 453
9.12 The Exists Cnditional Element = 456
9.13 The Forall Conditional Element = 458
9.14 The Logical Conditional Element = 460
9.15 Utility Commands = 464
9.16 Summary = 467
CHAPTER 10 MODULAR DESIGN AND EXECUTION CONTROL = 473
10.1 Introduction = 473
10.2 Deftemplate Attributes = 473
10.3 Salience = 481
10.4 Phases And Control Facts = 484
10.5 Misuse Of Salience = 490
10.6 The Defmodule Construct = 492
10.7 Importing And Exporting Facts = 496
10.8 MOdules And Execution Control = 500
10.9 Summary = 508
CHAPTER 11 EFFICIENCY IN RULE-BASED LANGUAGES = 513
11.1 Introduction = 513
11.2 The Rete Pattern Matching Algorithm = 513
11.3 the Pattern Network = 517
11.4 The Join Network = 520
11.5 The Importance Of Pattern Order = 523
11.6 Ordering Patterns For Efficiency = 529
11.7 Multifield Variables And Efficiency = 530
11.8 The Test CE And Efficiency = 531
11.9 Built-In Pattern Matching Constraints = 533
11.10 General Rules Vs. Specific Rules = 533
11.11 Procedural Functions = 535
11.12 Simple Rules Vs. Complex Rules= 538
11.13 Loading And Saving Facts = 541
11.14 Summary = 542
CHAPTER 12 EXPERT SYSTEM DESIGN EXAMPLES = 547
12.1 Introduction = 547
12.2 Certainty Factors = 547
12.3 Decision Trees = 551
12.4 Backward Chaining = 565
12.5 A Monitoring Problem = 578
12.6 Summary = 594
APPENDIX A SOME USEFUL EQUIVALENCES = 597
APPENDIX B SOME ELEMENTARY QUANTIFIERS AND THEIR MEANING = 599
APPENDIX C SOME SET PROPERTIES = 601
APPENDIX D CLIPS SUPPORT INFORMATION = 603
APPENDIX E CLIPS COMMAND AND FUNCTION SUMMARY = 605
APPENDIX F THE MICROEMACS EDITOR = 619
APPENDIX G CLIPS BNF = 625
INDEX = 631
