Solving non-deterministic planning problems with pattern database heuristics

  • Authors:

  • Pascal Bercher;Robert Mattmüller

  • Affiliations:

  • Institut für Künstliche Intelligenz, Universität Ulm, Germany;Institut für Informatik, Albert-Ludwigs-Universität Freiburg, Germany

  • Venue:
  • KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
  • Year:
  • 2009

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Abstract

Non-determinism arises naturally in many real-world applications of action planning. Strong plans for this type of problems can be found using AO* search guided by an appropriate heuristic function. Most domain-independent heuristics considered in this context so far are based on the idea of ignoring delete lists and do not properly take the non-determinism into account. Therefore, we investigate the applicability of pattern database (PDB) heuristics to nondeterministic planning. PDB heuristics have emerged as rather informative in a deterministic context. Our empirical results suggest that PDB heuristics can also perform reasonably well in non-deterministic planning. Additionally, we present a generalization of the pattern additivity criterion known from classical planning to the non-deterministic setting.