Concise finite-domain representations for PDDL planning tasks

  • Authors:

  • Malte Helmert

  • Affiliations:

  • Institut für Informatik, Albert-Ludwigs-Universität Freiburg, Georges-Köhler-Allee 052, 79110 Freiburg, Germany

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2009

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Abstract

We introduce an efficient method for translating planning tasks specified in the standard PDDL formalism into a concise grounded representation that uses finite-domain state variables instead of the straight-forward propositional encoding. Translation is performed in four stages. Firstly, we transform the input task into an equivalent normal form expressed in a restricted fragment of PDDL. Secondly, we synthesize invariants of the planning task that identify groups of mutually exclusive propositions which can be represented by a single finite-domain variable. Thirdly, we perform an efficient relaxed reachability analysis using logic programming techniques to obtain a grounded representation of the input. Finally, we combine the results of the third and fourth stage to generate the final grounded finite-domain representation. The presented approach has originally been implemented as part of the Fast Downward planning system for the 4th International Planning Competition (IPC4). Since then, it has been used in a number of other contexts with considerable success, and the use of concise finite-domain representations has become a common feature of state-of-the-art planners.