Introduction to Knowledge Systems (eBook)
896 Seiten
Elsevier Science (Verlag)
978-0-08-050916-7 (ISBN)
Focusing on fundamental scientific and engineering issues, this book communicates the principles of building and using knowledge systems from the conceptual standpoint as well as the practical.
Previous treatments of knowledge systems have focused on applications within a particular field, or on symbol-level representations, such as the use of frame and rule representations. Introduction to Knowledge Systems presents fundamentals of symbol-level representations including
representations for time, space, uncertainty, and vagueness. It also compares the knowledge-level organizations for three common knowledge-intensive tasks: classification, configuration, and diagnosis.
The art of building knowledge systems incorporates computer science theory, programming practice, and psychology. The scope of this book is appropriately broad, ranging from the design of hierarchical search algorithms to techniques for acquiring the task-specific knowledge needed for successful applications.
Each chapter proceeds from concepts to applications, and closes with a brief tour of current research topics and open issues. Readers will come away with a solid foundation that will enable them to create real-world knowledge systems using whatever tools and programming languages are most current and appropriate.
Focusing on fundamental scientific and engineering issues, this book communicates the principles of building and using knowledge systems from the conceptual standpoint as well as the practical. Previous treatments of knowledge systems have focused on applications within a particular field, or on symbol-level representations, such as the use of frame and rule representations. Introduction to Knowledge Systems presents fundamentals of symbol-level representations including representations for time, space, uncertainty, and vagueness. It also compares the knowledge-level organizations for three common knowledge-intensive tasks: classification, configuration, and diagnosis. The art of building knowledge systems incorporates computer science theory, programming practice, and psychology. The scope of this book is appropriately broad, ranging from the design of hierarchical search algorithms to techniques for acquiring the task-specific knowledge needed for successful applications. Each chapter proceeds from concepts to applications, and closes with a brief tour of current research topics and open issues. Readers will come away with a solid foundation that will enable them to create real-world knowledge systems using whatever tools and programming languages are most current and appropriate.
Front Cover 1
Introduction to Knowledge Systems 2
Table of Contents 6
Dedication 4
Foreword 14
Preface 16
Notes on the Exercises 20
Introduction and Overview 22
PART I: FOUNDATIONS 40
Chapter 1. Symbol Systems 42
1.1 Symbols and Symbol Structures 43
1.2 Semantics: The Meanings of Symbols 56
1.3 Modeling: Dimensions of Representation 89
1.4 Programs: Patterns, Simplicity, and Expressiveness 128
1.5 Quandaries and Open Issues 157
Chapter 2. Search and Problem Solving 167
2.1 Concepts of Search 168
2.2 Blind Search 186
2.3 Directed Search 224
2.4 Hierarchical Search 280
2.5 Quandaries and Open Issues 308
Chapter 3. Knowledge and Software Engineering 312
3.1 Understanding Knowledge Systems in Context 313
3.2 Formulating Expertise 335
3.3 Collaboratively Articulating Work Practices 357
3.4 Knowledge versus Complexity 386
3.5 Open Issues and Quandaries 415
PART II: THE SYMBOL LEVEL 424
Chapter 4. Reasoning about Time 426
4.1 Temporal Concepts 428
4.2 Continuous versus Discrete Temporal Models 431
4.3 Temporal Uncertainty and Constraint Reasoning 432
4.4 Branching Time 442
4.5 Summary and Review 444
4.6 Open Issues and Quandaries 448
Chapter 5. Reasoning about Space 453
5.1 Spatial Concepts 454
5.2 Spatial Search 456
5.3 Reasoning about Shape 463
5.4 The Piano Example: Using Multiple Representations of Space 465
5.5 Summary and Review 473
5.6 Open Issues and Quandries 479
Chapter 6. Reasoning about Uncertainty and Vagueness 481
6.1 Representing Uncertainty 482
6.2 Representing Vagueness 538
6.3 Open Issues and Quandries 554
PART III: THE KNOWLEDGE LEVEL 562
Chapter 7. Classification 564
7.1 Introduction 564
7.2 Models for Classification Domains 568
7.3 Case Studies of Classification Systems 584
7.4 Knowledge and Methods for Classification 609
7.5 Open Issues and Quandaries 625
Chapter 8. Configuration 629
8.1 Introduction 629
8.2 Models for Configuration Domains 633
8.3 Case Studies of Configuration Systems 646
8.4 Methods for Configuration Problems 677
8.5 Open Issues and Quandaries 688
Chapter 9. Diagnosis and Troubleshooting 691
9.1 Introduction 691
9.2 Models for Diagnosis Domains 694
9.3 Case Studies of Diagnosis and Troubleshooting Systems 732
9.4 Knowledge and Methods for Diagnosis 785
9.5 Open Issues and Quandaries 792
A: Annotated Bibliographies by Chapter 797
A.1 Further Reading on Symbol Systems (Chapter 1) 797
A.2 Further Reading on Search and Problem Solving (Chapter 2) 805
A.3 Further Reading on Knowledge and Software Engineering (Chapter 3) 809
A.4 Further Reading on Models of Time (Chapter 4) 814
A.5 Further Readings on Models of Space (Chapter 5) 817
A.6 Further Readings on Models of Uncertainty and Vagueness (Chapter 6) 818
A.7 Further Reading on Classification (Chapter 7) 822
A.8 Further Reading on Configuration (Chapter 8) 824
A.9 Further Reading on Diagnosis and Troubleshooting (Chapter 9) 826
B: Selected Answers to Exercises 832
B.1 Chapter 1 832
B.2 Chapter 2 839
B.3 Chapter 3 846
B.4 Chapter 4 852
..5 Chapter 5 855
B.6 Chapter 6 856
B.7 Chapter 7 861
B.8 Chapter 8 862
B.9 Chapter 9 866
Index 874
| Erscheint lt. Verlag | 28.6.2014 |
|---|---|
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Nachrichtentechnik | |
| ISBN-10 | 0-08-050916-9 / 0080509169 |
| ISBN-13 | 978-0-08-050916-7 / 9780080509167 |
| Haben Sie eine Frage zum Produkt? |
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