Principles of Artificial Intelligence - 1st Edition - ISBN: 9780934613101, 9781483295862

Principles of Artificial Intelligence

1st Edition

Authors: Nils Nilsson
eBook ISBN: 9781483295862
Imprint: Morgan Kaufmann
Published Date: 1st February 1982
Page Count: 476
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Description

A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used.

Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.

Table of Contents

Principles of Artificial Intelligence
by Nils Nilsson
    Preface
    Acknowledgements
    Credits
    Prologue
      0.1 Some Applications of Artificial Intelligence
      0.2 Overview
      0.3 Bibliography and Historical Remarks

    CHAPTER 1: PRODUCTION SYSTEMS AND AI
      1.1 Production Systems
      1.2 Specialized Production Systems
      1.3 Comments on the Different Types of Production Systems
      1.4 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 2: SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS
      2.1 Backtracking Strategies
      2.2 Graph-search Strategies
      2.3 Ununiformed Graph-search Procedures
      2.4 Heuristic Graph-search Procedures
      2.5 Related Algorithms
      2.6 Measures of Performance
      2.7 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 3: SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS
      3.1 Searching AND/OR Graphs
      3.2 AO*: A Heuristic Search Procedure for AND/OR Graphs
      3.3 Some Relationships Between Decomposable and Commutative Systems
      3.4 Searching Game Trees
      3.5 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 4: THE PREDICATE CALCULUS IN AI
      4.1 Informal Introduction to the Predicate Calculus
      4.2 Resolution
      4.3 The Use of the Predicate Calculus in AI
      4.4 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 5: RESOLUTION REFUTATION SYSTEMS
      5.1 Production Systems for Resolution Refutations
      5.2 Control Strategies for Resolution Methods
      5.3 Simplification Strategies
      5.4 Extracting Answers From Resolution Refutations
      5.5 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 6: Rule-Based Deduction Systems
      6.1 A Forward Deduction System
      6.2 A Backward Deduction System
      6.3 "Resolving" Within AND/OR Graphs
      6.4 Computation Deductions and Program Synthesis
      6.5 A Combination Forward and Backward System
      6.6 Control Knowledge For Rule-Based Deduction Systems
      6.7 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 7: BASIC PLAN-GENERATING SYSTEMS
      7.1 Robot Problem Solving
      7.2 A Forward Production System
      7.3 A Representation for Plans
      7.4 A Backward Preoduction System
      7.5 STRIPS
      7.6 Using Deduction Systems to Generate Robot Plans
      7.7 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 8: ADVANCED PLAN-GENERATING SYTEMS
      8.1 RSTRIPS
      8.2 DCOMP
      8.3 Amending Plans
      8.4 Hierarchical Planning
      8.5 Bibliographical and Historical Remarks
      Exercises

    CHAPTER 9: STRUCTURED OBJECT REPRESENTATIONS
      9.1 From Predicate Calculus to Units
      9.2 A Graphical Representation: Semantic Networks
      9.3 Matching
      9.4 Deductive Operations on Structured Objects
      9.5 Defaults and Contradictory Information
      9.6 Bibliographical and Historical Remarks
      Exercises

    Prospectus
      10.1 AI System Architectures
      10.2 Knowledge Acquisition
      10.3 Representational Formalisms
    Bibliography
    Author Index
    Subject Index

Details

No. of pages:
476
Language:
English
Copyright:
© Morgan Kaufmann 1982
Published:
Imprint:
Morgan Kaufmann
eBook ISBN:
9781483295862

About the Author

Nils Nilsson

Nils Nilsson

Nils J. Nilsson's long and rich research career has contributed much to AI. He has written many books, including the classic Principles of Artificial Intelligence. Dr. Nilsson is Kumagai Professor of Engineering, Emeritus, at Stanford University. He has served on the editorial boards of Artificial Intelligence and Machine Learning and as an Area Editor for the Journal of the Association for Computing Machinery. Former Chairman of the Department of Computer Science at Stanford, and former Director of the SRI Artificial Intelligence Center, he is also a past president and Fellow of the American Association for Artificial Intelligence.

Affiliations and Expertise

Stanford University