Engineering a conformant probabilistic planner

Authors:
Nilufer Onder;Garrett C. Whelan;Li Li
Affiliations:
Department of Computer Science, Michigan Technological University, Houghton, MI;Department of Computer Science, Michigan Technological University, Houghton, MI;Department of Computer Science, Michigan Technological University, Houghton, MI
Venue:
Journal of Artificial Intelligence Research
Year:
2006

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Abstract

We present a partial-order, conformant, probabilistic planner, Probapop which competed in the blind track of the Probabilistic Planning Competition in IPC-4. We explain how we adapt distance based heuristics for use with probabilistic domains. Probapop also incorporates heuristics based on probability of success. We explain the successes and diefficulties encountered during the design and implementation of Probapop.