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Universal Subgoaling and Chunking

The Automatic Generation and Learning of Goal Hierarchies

  • Book
  • © 1986

Overview

Authors:
  1. John Laird

    1. Xerox Palo Alto Research Center, Palo Alto, USA

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  2. Paul Rosenbloom

    1. Stanford University, Palo Alto, USA

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  3. Allen Newell

    1. Carnegie-Mellon University, Pittsburgh, USA

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Table of contents (18 chapters)

  1. Front Matter

    Pages i-xxi
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  2. Universal Subgoaling

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 3-16

    3. The Soar Architecture

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 17-55

    4. Empirical Demonstration

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 57-81

    5. Discussion

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 83-92

    6. Conclusion

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 93-94

  3. Back Matter

    Pages 95-131
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  4. The Chunking of Goal Hierarchies

    1. Front Matter

      Pages 133-133
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    2. Introduction

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 135-138

    3. Practice

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 139-148

    4. Stimulus-Response Compatibility

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 149-174

    5. Goal-Structured Models

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 175-199

    6. The XAPS3 Architecture

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 201-223

    7. Simulation Results

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 225-251

    8. Discussion

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 253-272

    9. Conclusion

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 273-274

  5. Back Matter

    Pages 275-282
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  6. Towards Chunking as a General Learning Mechanism

    1. Front Matter

      Pages 283-283
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    2. Introduction

      • John Laird, Paul Rosenbloom, Allen Newell
      Pages 285-286
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Keywords

About this book

Rarely do research paths diverge and converge as neatly and productively as the paths exemplified by the two efforts contained in this book. The story behind these researches is worth recounting. The story, as far as I'm concerned, starts back in the Fall of1976, when John Laird and Paul Rosenbloom, as new graduate students in computer science at Carnegie-Mellon University, joined the Instructible Production System (IPS) project (Rychener, Forgy, Langley, McDermott, Newell, Ramakrishna, 1977; Rychener & Newell, 1978). In those days, production systems were either small or special or both (Newell, 1973; Shortliffe, 1976). Mike Rychener had just completed his thesis (Rychener, 1976), showing how production systems could effectively and perspicuously program the full array of artificial intelligence (AI) systems, by creating versions of Studellt (done in an earlier study, Rychener 1975), EPAM, GPS, King-Pawn-King endgames, a toy-blocks problem solver, and a natural-language input system that connected to the blocks-world system.

Authors and Affiliations

  • Xerox Palo Alto Research Center, Palo Alto, USA

    John Laird

  • Stanford University, Palo Alto, USA

    Paul Rosenbloom

  • Carnegie-Mellon University, Pittsburgh, USA

    Allen Newell

Bibliographic Information

  • Book Title: Universal Subgoaling and Chunking

  • Book Subtitle: The Automatic Generation and Learning of Goal Hierarchies

  • Authors: John Laird, Paul Rosenbloom, Allen Newell

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

  • DOI: https://doi.org/10.1007/978-1-4613-2277-1

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Kluwer Academic Publishers 1986

  • Hardcover ISBN: 978-0-89838-213-6Published: 30 April 1986

  • Softcover ISBN: 978-1-4612-9405-4Published: 05 February 2012

  • eBook ISBN: 978-1-4613-2277-1Published: 06 December 2012

  • Series ISSN: 0893-3405

  • Edition Number: 1

  • Number of Pages: XXII, 314

  • Topics: Artificial Intelligence

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