A Counter-Example Based Approach to Probabilistic Conformant Planning
Keywords: probabilistic conformant planning, counter-examples, tags, probability, planning under uncertainty
TL;DR: A counter-example based approach to solve probabilistic conformant planning problems.
Abstract: This paper introduces a counter-example based approach for solving probabilistic conformant planning (PCP) problems. Our algorithm incrementally generates candidate plans and identifies counter-examples until it finds a plan for which the probability of success is above the specified threshold. We prove that the algorithm is sound and complete. We further propose a variation of our algorithm that uses hitting sets to accelerate the generation of candidate plans. Experimental results show that our planner is particularly suited for problems with a high probability threshold.
Primary Keywords: Knowledge Representation/Engineering
Category: Long
Student: Graduate
Supplemtary Material: zip
Submission Number: 164
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