Understanding Planning Tasks

Domain Complexity and Heuristic Decomposition

  • Authors
  • Malte¬†Helmert

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4929)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4929)

Table of contents

  1. Front Matter
  2. Planning Benchmarks

    1. Front Matter
      Pages 1-1
    2. Malte Helmert
      Pages 3-12
    3. Malte Helmert
      Pages 13-30
    4. Malte Helmert
      Pages 31-37
    5. Malte Helmert
      Pages 39-73
    6. Malte Helmert
      Pages 113-149
    7. Malte Helmert
      Pages 151-154
  3. Fast Downward

    1. Front Matter
      Pages 155-155
    2. Malte Helmert
      Pages 157-170
    3. Malte Helmert
      Pages 171-206
    4. Malte Helmert
      Pages 207-222
    5. Malte Helmert
      Pages 223-237
    6. Malte Helmert
      Pages 239-251
    7. Malte Helmert
      Pages 253-258
  4. Back Matter

About this book


Action planning has always played a central role in Artificial Intelligence. Given a description of the current situation, a description of possible actions and a description of the goals to be achieved, the task is to identify a sequence of actions, i.e., a plan that transforms the current situation into one that satisfies the goal description.

This monograph is a revised version of Malte Helmert's doctoral thesis, Solving Planning Tasks in Theory and Practice, written under the supervision of Professor Bernhard Nebel as thesis advisor at Albert-Ludwigs-Universit√§t Freiburg, Germany, in 2006. The book contains an exhaustive analysis of the computational complexity of the benchmark problems that have been used in the past decade, namely the standard benchmark domains of the International Planning Competitions (IPC). At the same time, it contributes to the practice of solving planning tasks by presenting a powerful new approach to heuristic planning. The author also provides an in-depth analysis of so-called routing and transportation problems.

All in all, this book will contribute significantly to advancing the state of the art in automatic planning.


Bernhard Nebel PDDL algorithmics approximation algorithms artificial intelligence classification complexity computational complexity graph theory heuristic search intelligence knowledge minimization optimization planning domains

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-540-77722-9
  • Online ISBN 978-3-540-77723-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site