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Learning Search Control Knowledge

An Explanation-Based Approach

  • Book
  • © 1988

Overview

Authors:
  1. Steven Minton

    1. Carnegie Mellon University, USA

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-x
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  2. Introduction

    • Steven Minton
    Pages 1-10

  3. Analyzing the Utility Problem

    • Steven Minton
    Pages 11-25

  4. Overview of the PRODIGY Problem Solver

    • Steven Minton
    Pages 27-50

  5. Specialization

    • Steven Minton
    Pages 51-62

  6. Compression

    • Steven Minton
    Pages 63-77

  7. Utility Evaluation

    • Steven Minton
    Pages 79-84

  8. Learning from Success

    • Steven Minton
    Pages 85-99

  9. Learning from Failure

    • Steven Minton
    Pages 101-113

  10. Learning from Goal Interactions

    • Steven Minton
    Pages 115-123

  11. Performance Results

    • Steven Minton
    Pages 125-150

  12. Proofs, Explanations, and Correctness: Putting It All Together

    • Steven Minton
    Pages 151-165

  13. Related Work

    • Steven Minton
    Pages 167-184

  14. Conclusion

    • Steven Minton
    Pages 185-189

  15. Back Matter

    Pages 191-214
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Keywords

About this book

The ability to learn from experience is a fundamental requirement for intelligence. One of the most basic characteristics of human intelligence is that people can learn from problem solving, so that they become more adept at solving problems in a given domain as they gain experience. This book investigates how computers may be programmed so that they too can learn from experience. Specifically, the aim is to take a very general, but inefficient, problem solving system and train it on a set of problems from a given domain, so that it can transform itself into a specialized, efficient problem solver for that domain. on a knowledge-intensive Recently there has been considerable progress made learning approach, explanation-based learning (EBL), that brings us closer to this possibility. As demonstrated in this book, EBL can be used to analyze a problem solving episode in order to acquire control knowledge. Control knowledge guides the problem solver's search by indicating the best alternatives to pursue at each choice point. An EBL system can produce domain specific control knowledge by explaining why the choices made during a problem solving episode were, or were not, appropriate.

Authors and Affiliations

  • Carnegie Mellon University, USA

    Steven Minton

Bibliographic Information

  • Book Title: Learning Search Control Knowledge

  • Book Subtitle: An Explanation-Based Approach

  • Authors: Steven Minton

  • Series Title: The Springer International Series in Engineering and Computer Science

  • DOI: https://doi.org/10.1007/978-1-4613-1703-6

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Kluwer Academic Publishers, Boston 1988

  • Hardcover ISBN: 978-0-89838-294-5Published: 31 October 1988

  • Softcover ISBN: 978-1-4612-8960-9Published: 05 October 2011

  • eBook ISBN: 978-1-4613-1703-6Published: 06 December 2012

  • Series ISSN: 0893-3405

  • Edition Number: 1

  • Number of Pages: X, 214

  • Topics: Artificial Intelligence

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