Constraint partitioning for solving planning problems with trajectory constraints and goal preferences

  • Authors:

  • Chih-Wei Hsu;Benjamin W. Wah;Ruoyun Huang;Yixin Chen

  • Affiliations:

  • Dept. of Electrical and Computer Engineering and the Coordinated Science Laboratory, University of Illinois, Urbana-Champaign, Urbana, IL;Dept. of Electrical and Computer Engineering and the Coordinated Science Laboratory, University of Illinois, Urbana-Champaign, Urbana, IL;Dept. of Computer Science and Engineering, Washington University in St Louis, St Louis, MO;Dept. of Computer Science and Engineering, Washington University in St Louis, St Louis, MO

  • Venue:
  • IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
  • Year:
  • 2007

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Abstract

The PDDL3 specifications include soft goals and trajectory constraints for distinguishing highquality plans among the many feasible plans in a solution space. To reduce the complexity of solving a large PDDL3 planning problem, constraint partitioning can be used to decompose its constraints into subproblems of much lower complexity. However, constraint locality due to soft goals and trajectory constraints cannot be effectively exploited by existing subgoal-partitioning techniques developed for solving PDDL2.2 problems. In this paper, we present an improved partition-andresolve strategy for supporting the new features in PDDL3. We evaluate techniques for resolving violated global constraints, optimizing goal preferences, and achieving subgoals in a multivalued representation. Empirical results on the 5th International Planning Competition (IPC5) benchmarks show that our approach is effective and significantly outperforms other competing planners.