Compiling conformant probabilistic planning problems into classical planning

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13 Scopus citations

Abstract

In CPP, we are given a set of actions (assumed deterministic in this paper), a distribution over initial states, a goal condition, and a real value 0 < θ ≤ 1. We seek a plan π such that following its execution, the goal probability is at least θ. Motivated by the success of the translation-based approach for conformant planning, introduced by Palacios and Geffner, we suggest a new compilation scheme from CPP to classical planning. Our compilation scheme maps CPP into cost-bounded classical planning, where the cost-bound represents the maximum allowed probability of failure. Empirically, this technique shows mixed, but promising results, performing very well on some domains, and less so on others when compared to the state of the art PFF planner. It is also very flexible due to its generic nature, allowing us to experiment with diverse search strategies developed for classical planning. Our results show that compilation-based technique offer a new viable approach to CPP and, possibly, more general probabilistic planning problems.

Original languageEnglish
Title of host publicationICAPS 2013 - Proceedings of the 23rd International Conference on Automated Planning and Scheduling
Pages197-205
Number of pages9
StatePublished - 13 Dec 2013
Event23rd International Conference on Automated Planning and Scheduling, ICAPS 2013 - Rome, Italy
Duration: 10 Jun 201314 Jun 2013

Publication series

NameICAPS 2013 - Proceedings of the 23rd International Conference on Automated Planning and Scheduling

Conference

Conference23rd International Conference on Automated Planning and Scheduling, ICAPS 2013
Country/TerritoryItaly
CityRome
Period10/06/1314/06/13

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