Non-Deterministic Conformant Planning Using a Counterexample-Guided Incremental Compilation to Classical Planning

Authors

  • Enrico Scala University of Brescia, Italy
  • Alban Grastien Australian National University, Australia

Keywords:

Conformant, Contingent And Adversarial Planning

Abstract

We address the problem of non-deterministic conformant planning, i.e., finding a plan in a non-deterministic context where the environment is not observable. Our approach uses an unsound but complete reduction from non-deterministic conformant planning to classical planning to find a candidate plan; the validity of this plan is then verified by a SAT solver; if the plan is invalid, the reduction is revised to guarantee that the invalid plan will not be valid in the classical planning problem. This procedure is executed until a valid plan is found, or it is shown that there is no plan. Experiments show that this approach provides a nice trade-off between fast but unsound, and complete but slow approaches.

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Published

2021-05-17

How to Cite

Scala, E., & Grastien, A. (2021). Non-Deterministic Conformant Planning Using a Counterexample-Guided Incremental Compilation to Classical Planning. Proceedings of the International Conference on Automated Planning and Scheduling, 31(1), 299-307. Retrieved from https://ojs.aaai.org/index.php/ICAPS/article/view/15974