Introduction to Knowledge Systems

Introduction to Knowledge Systems

by Mark Stefik
Released June 2014
Publisher(s): Morgan Kaufmann
ISBN: 9780080509167

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Book description

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.

Table of contents

  1. Front Cover
  2. Introduction to Knowledge Systems
  3. Table of Contents
  4. Dedication
  5. Foreword
  6. Preface
  7. Notes on the Exercises
  8. Introduction and Overview (1/4)
  9. Introduction and Overview (2/4)
  10. Introduction and Overview (3/4)
  11. Introduction and Overview (4/4)
  12. PART I: FOUNDATIONS
    1. Chapter 1. Symbol Systems
      1. 1.1 Symbols and Symbol Structures (1/3)
      2. 1.1 Symbols and Symbol Structures (2/3)
      3. 1.1 Symbols and Symbol Structures (3/3)
      4. 1.2 Semantics: The Meanings of Symbols (1/7)
      5. 1.2 Semantics: The Meanings of Symbols (2/7)
      6. 1.2 Semantics: The Meanings of Symbols (3/7)
      7. 1.2 Semantics: The Meanings of Symbols (4/7)
      8. 1.2 Semantics: The Meanings of Symbols (5/7)
      9. 1.2 Semantics: The Meanings of Symbols (6/7)
      10. 1.2 Semantics: The Meanings of Symbols (7/7)
      11. 1.3 Modeling: Dimensions of Representation (1/8)
      12. 1.3 Modeling: Dimensions of Representation (2/8)
      13. 1.3 Modeling: Dimensions of Representation (3/8)
      14. 1.3 Modeling: Dimensions of Representation (4/8)
      15. 1.3 Modeling: Dimensions of Representation (5/8)
      16. 1.3 Modeling: Dimensions of Representation (6/8)
      17. 1.3 Modeling: Dimensions of Representation (7/8)
      18. 1.3 Modeling: Dimensions of Representation (8/8)
      19. 1.4 Programs: Patterns, Simplicity, and Expressiveness (1/6)
      20. 1.4 Programs: Patterns, Simplicity, and Expressiveness (2/6)
      21. 1.4 Programs: Patterns, Simplicity, and Expressiveness (3/6)
      22. 1.4 Programs: Patterns, Simplicity, and Expressiveness (4/6)
      23. 1.4 Programs: Patterns, Simplicity, and Expressiveness (5/6)
      24. 1.4 Programs: Patterns, Simplicity, and Expressiveness (6/6)
      25. 1.5 Quandaries and Open Issues (1/2)
      26. 1.5 Quandaries and Open Issues (2/2)
    2. Chapter 2. Search and Problem Solving
      1. 2.1 Concepts of Search (1/4)
      2. 2.1 Concepts of Search (2/4)
      3. 2.1 Concepts of Search (3/4)
      4. 2.1 Concepts of Search (4/4)
      5. 2.2 Blind Search (1/8)
      6. 2.2 Blind Search (2/8)
      7. 2.2 Blind Search (3/8)
      8. 2.2 Blind Search (4/8)
      9. 2.2 Blind Search (5/8)
      10. 2.2 Blind Search (6/8)
      11. 2.2 Blind Search (7/8)
      12. 2.2 Blind Search (8/8)
      13. 2.3 Directed Search (1/12)
      14. 2.3 Directed Search (2/12)
      15. 2.3 Directed Search (3/12)
      16. 2.3 Directed Search (4/12)
      17. 2.3 Directed Search (5/12)
      18. 2.3 Directed Search (6/12)
      19. 2.3 Directed Search (7/12)
      20. 2.3 Directed Search (8/12)
      21. 2.3 Directed Search (9/12)
      22. 2.3 Directed Search (10/12)
      23. 2.3 Directed Search (11/12)
      24. 2.3 Directed Search (12/12)
      25. 2.4 Hierarchical Search (1/6)
      26. 2.4 Hierarchical Search (2/6)
      27. 2.4 Hierarchical Search (3/6)
      28. 2.4 Hierarchical Search (4/6)
      29. 2.4 Hierarchical Search (5/6)
      30. 2.4 Hierarchical Search (6/6)
      31. 2.5 Quandaries and Open Issues
    3. Chapter 3. Knowledge and Software Engineering
      1. 3.1 Understanding Knowledge Systems in Context (1/5)
      2. 3.1 Understanding Knowledge Systems in Context (2/5)
      3. 3.1 Understanding Knowledge Systems in Context (3/5)
      4. 3.1 Understanding Knowledge Systems in Context (4/5)
      5. 3.1 Understanding Knowledge Systems in Context (5/5)
      6. 3.2 Formulating Expertise (1/5)
      7. 3.2 Formulating Expertise (2/5)
      8. 3.2 Formulating Expertise (3/5)
      9. 3.2 Formulating Expertise (4/5)
      10. 3.2 Formulating Expertise (5/5)
      11. 3.3 Collaboratively Articulating Work Practices (1/6)
      12. 3.3 Collaboratively Articulating Work Practices (2/6)
      13. 3.3 Collaboratively Articulating Work Practices (3/6)
      14. 3.3 Collaboratively Articulating Work Practices (4/6)
      15. 3.3 Collaboratively Articulating Work Practices (5/6)
      16. 3.3 Collaboratively Articulating Work Practices (6/6)
      17. 3.4 Knowledge versus Complexity (1/6)
      18. 3.4 Knowledge versus Complexity (2/6)
      19. 3.4 Knowledge versus Complexity (3/6)
      20. 3.4 Knowledge versus Complexity (4/6)
      21. 3.4 Knowledge versus Complexity (5/6)
      22. 3.4 Knowledge versus Complexity (6/6)
      23. 3.5 Open Issues and Quandaries (1/2)
      24. 3.5 Open Issues and Quandaries (2/2)
  13. PART II: THE SYMBOL LEVEL
    1. Chapter 4. Reasoning about Time
      1. 4.1 Temporal Concepts
      2. 4.2 Continuous versus Discrete Temporal Models
      3. 4.3 Temporal Uncertainty and Constraint Reasoning (1/2)
      4. 4.3 Temporal Uncertainty and Constraint Reasoning (2/2)
      5. 4.4 Branching Time
      6. 4.5 Summary and Review
      7. 4.6 Open Issues and Quandaries
    2. Chapter 5. Reasoning about Space
      1. 5.1 Spatial Concepts
      2. 5.2 Spatial Search (1/2)
      3. 5.2 Spatial Search (2/2)
      4. 5.3 Reasoning about Shape
      5. 5.4 The Piano Example: Using Multiple Representations of Space (1/2)
      6. 5.4 The Piano Example: Using Multiple Representations of Space (2/2)
      7. 5.5 Summary and Review (1/2)
      8. 5.5 Summary and Review (2/2)
      9. 5.6 Open Issues and Quandries
    3. Chapter 6. Reasoning about Uncertainty and Vagueness
      1. 6.1 Representing Uncertainty (1/12)
      2. 6.1 Representing Uncertainty (2/12)
      3. 6.1 Representing Uncertainty (3/12)
      4. 6.1 Representing Uncertainty (4/12)
      5. 6.1 Representing Uncertainty (5/12)
      6. 6.1 Representing Uncertainty (6/12)
      7. 6.1 Representing Uncertainty (7/12)
      8. 6.1 Representing Uncertainty (8/12)
      9. 6.1 Representing Uncertainty (9/12)
      10. 6.1 Representing Uncertainty (10/12)
      11. 6.1 Representing Uncertainty (11/12)
      12. 6.1 Representing Uncertainty (12/12)
      13. 6.2 Representing Vagueness (1/4)
      14. 6.2 Representing Vagueness (2/4)
      15. 6.2 Representing Vagueness (3/4)
      16. 6.2 Representing Vagueness (4/4)
      17. 6.3 Open Issues and Quandries (1/2)
      18. 6.3 Open Issues and Quandries (2/2)
  14. PART III: THE KNOWLEDGE LEVEL
  15. Chapter 7. Classification
    1. 7.1 Introduction
    2. 7.2 Models for Classification Domains (1/4)
    3. 7.2 Models for Classification Domains (2/4)
    4. 7.2 Models for Classification Domains (3/4)
    5. 7.2 Models for Classification Domains (4/4)
    6. 7.3 Case Studies of Classification Systems (1/5)
    7. 7.3 Case Studies of Classification Systems (2/5)
    8. 7.3 Case Studies of Classification Systems (3/5)
    9. 7.3 Case Studies of Classification Systems (4/5)
    10. 7.3 Case Studies of Classification Systems (5/5)
    11. 7.4 Knowledge and Methods for Classification (1/4)
    12. 7.4 Knowledge and Methods for Classification (2/4)
    13. 7.4 Knowledge and Methods for Classification (3/4)
    14. 7.4 Knowledge and Methods for Classification (4/4)
    15. 7.5 Open Issues and Quandaries
  16. Chapter 8. Configuration
    1. 8.1 Introduction
    2. 8.2 Models for Configuration Domains (1/3)
    3. 8.2 Models for Configuration Domains (2/3)
    4. 8.2 Models for Configuration Domains (3/3)
    5. 8.3 Case Studies of Configuration Systems (1/7)
    6. 8.3 Case Studies of Configuration Systems (2/7)
    7. 8.3 Case Studies of Configuration Systems (3/7)
    8. 8.3 Case Studies of Configuration Systems (4/7)
    9. 8.3 Case Studies of Configuration Systems (5/7)
    10. 8.3 Case Studies of Configuration Systems (6/7)
    11. 8.3 Case Studies of Configuration Systems (7/7)
    12. 8.4 Methods for Configuration Problems (1/3)
    13. 8.4 Methods for Configuration Problems (2/3)
    14. 8.4 Methods for Configuration Problems (3/3)
    15. 8.5 Open Issues and Quandaries
  17. Chapter 9. Diagnosis and Troubleshooting
    1. 9.1 Introduction
    2. 9.2 Models for Diagnosis Domains (1/8)
    3. 9.2 Models for Diagnosis Domains (2/8)
    4. 9.2 Models for Diagnosis Domains (3/8)
    5. 9.2 Models for Diagnosis Domains (4/8)
    6. 9.2 Models for Diagnosis Domains (5/8)
    7. 9.2 Models for Diagnosis Domains (6/8)
    8. 9.2 Models for Diagnosis Domains (7/8)
    9. 9.2 Models for Diagnosis Domains (8/8)
    10. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (1/11)
    11. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (2/11)
    12. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (3/11)
    13. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (4/11)
    14. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (5/11)
    15. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (6/11)
    16. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (7/11)
    17. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (8/11)
    18. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (9/11)
    19. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (10/11)
    20. 9.3 Case Studies of Diagnosis and Troubleshooting Systems (11/11)
    21. 9.4 Knowledge and Methods for Diagnosis (1/2)
    22. 9.4 Knowledge and Methods for Diagnosis (2/2)
    23. 9.5 Open Issues and Quandaries
  18. A: Annotated Bibliographies by Chapter
    1. A.1 Further Reading on Symbol Systems (Chapter 1)
    2. A.2 Further Reading on Search and Problem Solving (Chapter 2)
    3. A.3 Further Reading on Knowledge and Software Engineering (Chapter 3)
    4. A.4 Further Reading on Models of Time (Chapter 4)
    5. A.5 Further Readings on Models of Space (Chapter 5)
    6. A.6 Further Readings on Models of Uncertainty and Vagueness (Chapter 6)
    7. A.7 Further Reading on Classification (Chapter 7)
    8. A.8 Further Reading on Configuration (Chapter 8)
    9. A.9 Further Reading on Diagnosis and Troubleshooting (Chapter 9) (1/2)
    10. A.9 Further Reading on Diagnosis and Troubleshooting (Chapter 9) (2/2)
  19. B: Selected Answers to Exercises
    1. B.1 Chapter 1
    2. B.2 Chapter 2 (1/2)
    3. B.2 Chapter 2 (2/2)
    4. B.3 Chapter 3 (1/2)
    5. B.3 Chapter 3 (2/2)
    6. B.4 Chapter 4
    7. Β.5 Chapter 5
    8. B.6 Chapter 6
    9. B.7 Chapter 7
    10. B.8 Chapter 8
    11. B.9 Chapter 9 (1/2)
    12. B.9 Chapter 9 (2/2)
  20. Index (1/4)
  21. Index (2/4)
  22. Index (3/4)
  23. Index (4/4)

Product information

  • Title: Introduction to Knowledge Systems
  • Author(s): Mark Stefik
  • Release date: June 2014
  • Publisher(s): Morgan Kaufmann
  • ISBN: 9780080509167