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Knowledge Representation and Reasoning

Book Description

Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed.

This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs.

*Authors are well-recognized experts in the field who have applied the techniques to real-world problems
* Presents the core ideas of KR&R in a simple straight forward approach, independent of the quirks of research systems
*Offers the first true synthesis of the field in over a decade

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. About the Authors
  6. Preface
  7. Acknowledgments
  8. Table of Contents
  9. Chapter 1: Introduction
    1. 1.1 THE KEY CONCEPTS: KNOWLEDGE, REPRESENTATION, AND REASONING
    2. 1.2 WHY KNOWLEDGE REPRESENTATION AND REASONING?
    3. 1.3 THE ROLE OF LOGIC
    4. 1.4 BIBLIOGRAPHIC NOTES
    5. 1.5 EXERCISES
  10. Chapter 2: The Language of First-Order Logic
    1. 2.1 INTRODUCTION
    2. 2.2 THE SYNTAX
    3. 2.3 THE SEMANTICS
    4. 2.4 THE PRAGMATICS
    5. 2.5 EXPLICIT AND IMPLICIT BELIEF
    6. 2.6 BIBLIOGRAPHIC NOTES
    7. 2.7 EXERCISES
  11. Chapter 3: Expressing Knowledge
    1. 3.1 KNOWLEDGE ENGINEERING
    2. 3.2 VOCABULARY
    3. 3.3 BASIC FACTS
    4. 3.4 COMPLEX FACTS
    5. 3.5 TERMINOLOGICAL FACTS
    6. 3.6 ENTAILMENTS
    7. 3.7 ABSTRACT INDIVIDUALS
    8. 3.8 OTHER SORTS OF FACTS
    9. 3.9 BIBLIOGRAPHIC NOTES
    10. 3.10 EXERCISES
  12. Chapter 4: Resolution
    1. 4.1 THE PROPOSITIONAL CASE
    2. 4.2 HANDLING VARIABLES AND QUANTIFIERS
    3. 4.3 DEALING WITH COMPUTATIONAL INTRACTABILITY
    4. 4.4 BIBLIOGRAPHIC NOTES
    5. 4.5 EXERCISES
  13. Chapter 5: Reasoning with Horn Clauses
    1. 5.1 HORN CLAUSES
    2. 5.2 SLD RESOLUTION
    3. 5.3 COMPUTING SLD DERIVATIONS
    4. 5.4 BIBLIOGRAPHIC NOTES
    5. 5.5 EXERCISES
  14. Chapter 6: Procedural Control of Reasoning
    1. 6.1 FACTS AND RULES
    2. 6.2 RULE FORMATION AND SEARCH STRATEGY
    3. 6.3 ALGORITHM DESIGN
    4. 6.4 SPECIFYING GOAL ORDER
    5. 6.5 COMMITTING TO PROOF METHODS
    6. 6.6 CONTROLLING BACKTRACKING
    7. 6.7 NEGATION AS FAILURE
    8. 6.8 DYNAMIC DATABASES
    9. 6.9 BIBLIOGRAPHIC NOTES
    10. 6.10 EXERCISES
  15. Chapter 7: Rules in Production Systems
    1. 7.1 PRODUCTION SYSTEMS: BASIC OPERATION
    2. 7.2 WORKING MEMORY
    3. 7.3 PRODUCTION RULES
    4. 7.4 A FIRST EXAMPLE
    5. 7.5 A SECOND EXAMPLE
    6. 7.6 CONFLICT RESOLUTION
    7. 7.7 MAKING PRODUCTION SYSTEMS MORE EFFICIENT
    8. 7.8 APPLICATIONS AND ADVANTAGES
    9. 7.9 SOME SIGNIFICANT PRODUCTION RULE SYSTEMS
    10. 7.10 BIBLIOGRAPHIC NOTES
    11. 7.11 EXERCISES
  16. Chapter 8: Object-Oriented Representation
    1. 8.1 OBJECTS AND FRAMES
    2. 8.2 A BASIC FRAME FORMALISM
    3. 8.3 AN EXAMPLE: USING FRAMES TO PLAN A TRIP
    4. 8.4 BEYOND THE BASICS
    5. 8.5 BIBLIOGRAPHIC NOTES
    6. 8.6 EXERCISES
  17. Chapter 9: Structured Descriptions
    1. 9.1 DESCRIPTIONS
    2. 9.2 A DESCRIPTION LANGUAGE
    3. 9.3 MEANING AND ENTAILMENT
    4. 9.4 COMPUTING ENTAILMENTS
    5. 9.5 TAXONOMIES AND CLASSIFICATION
    6. 9.6 BEYOND THE BASICS
    7. 9.7 BIBLIOGRAPHIC NOTES
    8. 9.8 EXERCISES
  18. Chapter 10: Inheritance
    1. 10.1 INHERITANCE NETWORKS
    2. 10.2 STRATEGIES FOR DEFEASIBLE INHERITANCE
    3. 10.3 A FORMAL ACCOUNT OF INHERITANCE NETWORKS
    4. 10.4 BIBLIOGRAPHIC NOTES
    5. 10.5 EXERCISES
  19. Chapter 11: Defaults
    1. 11.1 INTRODUCTION
    2. 11.2 CLOSED-WORLD REASONING
    3. 11.3 CIRCUMSCRIPTION
    4. 11.4 DEFAULT LOGIC
    5. 11.5 AUTOEPISTEMIC LOGIC
    6. 11.6 CONCLUSION
    7. 11.7 BIBLIOGRAPHIC NOTES
    8. 11.8 EXERCISES
  20. Chapter 12: Vagueness, Uncertainty, and Degrees of Belief
    1. 12.1 NONCATEGORICAL REASONING
    2. 12.2 OBJECTIVE PROBABILITY
    3. 12.3 SUBJECTIVE PROBABILITY
    4. 12.4 VAGUENESS
    5. 12.5 BIBLIOGRAPHIC NOTES
    6. 12.6 EXERCISES
  21. Chapter 13: Explanation and Diagnosis
    1. 13.1 DIAGNOSIS
    2. 13.2 EXPLANATION
    3. 13.3 A CIRCUIT EXAMPLE
    4. 13.4 BEYOND THE BASICS
    5. 13.5 BIBLIOGRAPHIC NOTES
    6. 13.6 EXERCISES
  22. Chapter 14: Actions
    1. 14.1 THE SITUATION CALCULUS
    2. 14.2 A SIMPLE SOLUTION TO THE FRAME PROBLEM
    3. 14.3 COMPLEX ACTIONS
    4. 14.4 BIBLIOGRAPHIC NOTES
    5. 14.5 EXERCISES
  23. Chapter 15: Planning
    1. 15.1 PLANNING IN THE SITUATION CALCULUS
    2. 15.2 THE STRIPS REPRESENTATION
    3. 15.3 PLANNING AS A REASONING TASK
    4. 15.4 BEYOND THE BASICS
    5. 15.5 BIBLIOGRAPHIC NOTES
    6. 15.6 EXERCISES
  24. Chapter 16: The Tradeoff between Expressiveness and Tractability
    1. 16.1 A DESCRIPTION LOGIC CASE STUDY
    2. 16.2 LIMITED LANGUAGES
    3. 16.3 WHAT MAKES REASONING HARD?
    4. 16.4 VIVID KNOWLEDGE
    5. 16.5 BEYOND VIVID
    6. 16.6 BIBLIOGRAPHIC NOTES
    7. 16.7 EXERCISES
  25. Bibliography
  26. Index
  27. Instructions for online access