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Utilizing Problem Structure in Planning

A Local Search Approach

  • Book
  • © 2003

Overview

Authors:
  1. Jörg Hoffmann

    1. STI Innsbruck, Austria

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2854)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Table of contents (12 chapters)

  1. Front Matter

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  2. Planning: Motivation, Definitions, Methodology

    1. Front Matter

      Pages 1-1
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    2. Chapter 1: Introduction

      • Jörg Hoffmann
      Pages 3-10

    3. Chapter 2: Planning

      • Jörg Hoffmann
      Pages 11-31

  3. A Local Search Approach

    1. Front Matter

      Pages 33-33
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    2. Chapter 3: Base Architecture

      • Jörg Hoffmann
      Pages 35-73

    3. Chapter 4: Dead Ends

      • Jörg Hoffmann
      Pages 75-88

    4. Chapter 5: Goal Orderings

      • Jörg Hoffmann
      Pages 89-105

    5. Chapter 6: The AIPS-2000 Competition

      • Jörg Hoffmann
      Pages 107-112

  4. Local Search Topology

    1. Front Matter

      Pages 113-113
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    2. Chapter 7: Gathering Insights

      • Jörg Hoffmann
      Pages 115-134

    3. Chapter 8: Verifying the h  +  Hypotheses

      • Jörg Hoffmann
      Pages 135-180

    4. Chapter 9: Supporting the h FF Hypotheses

      • Jörg Hoffmann
      Pages 181-197

    5. Chapter 10: Discussion

      • Jörg Hoffmann
      Pages 199-202

    6. Appendix A: Formalized Benchmark Domains

      • Jörg Hoffmann
      Pages 203-233

    7. Appendix B: Automated Instance Generation

      • Jörg Hoffmann
      Pages 235-241

  5. Back Matter

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Keywords

About this book

Planning is a crucial skill for any autonomous agent, be it a physically embedded agent, such as a robot, or a purely simulated software agent. For this reason, planning, as a central research area of artificial intelligence from its beginnings, has gained even more attention and importance recently.

After giving a general introduction to AI planning, the book describes and carefully evaluates the algorithmic techniques used in fast-forward planning systems (FF), demonstrating their excellent performance in many wellknown benchmark domains. In advance, an original and detailed investigation identifies the main patterns of structure which cause the performance of FF, categorizing planning domains in a taxonomy of different classes with respect to their aptitude for being solved by heuristic approaches, such as FF. As shown, the majority of the planning benchmark domains lie in classes which are easy to solve.

Authors and Affiliations

  • STI Innsbruck, Austria

    Jörg Hoffmann

Bibliographic Information

  • Book Title: Utilizing Problem Structure in Planning

  • Book Subtitle: A Local Search Approach

  • Authors: Jörg Hoffmann

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/b93903

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2003

  • Softcover ISBN: 978-3-540-20259-2Published: 10 October 2003

  • eBook ISBN: 978-3-540-39607-9Published: 24 October 2003

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XVIII, 254

  • Topics: Artificial Intelligence, Algorithm Analysis and Problem Complexity

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