GPT Meets PSR

Blai Bonet and Sylvie Thiebaux

We present a case study in confronting the GPT generalpurpose planner with the challenging power supply restoration (PSR) benchmark for contingent planning. PSR is derived from a real-world problem, and the difficulty of modeling and solving it contrasts with that of the purely artificial benchmarks commonly used in the literature. This confrontation leads us to improve general techniques for contingent planning, to provide a PDDL-syle encoding of PSR which we hope to see used in planning competitions, and to report the first results on generating optimal policies for PSR.


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