Cost-optimal external planning

  • Authors:

  • Stefan Edelkamp;Shahid Jabbar

  • Affiliations:

  • Computer Science Department, University of Dortmund, Dortmund, Germany;Computer Science Department, University of Dortmund, Dortmund, Germany

  • Venue:
  • AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
  • Year:
  • 2006

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Abstract

This paper considers strategies for external memory based optimal planning. An external breadth-first search exploration algorithm is devised that is guaranteed to find the costoptimal solution. We contribute a procedure for finding the upper bound on the locality of the search in planning graphs that dictates the number of layers that have to be kept to avoid re-openings. We also discuss an external variant of Enforced Hill Climbing. Using relaxed-plan heuristic without helpful-action pruning we have been able to perform large explorations on metric planning problems, providing better plan lengths than have been reported earlier. A novel approach to plan reconstruction in external setting with linear I/O complexity is proposed. We provide external exploration results on some recently proposed planning domains.