APPSSAT: Approximate Probabilistic Planning Using Stochastic Satisfiability

Abstract

We describe APPSSAT, an anytime probabilistic contingent planner based on ZANDER, a probabilistic contingent planner that operates by converting the planning problem to a stochastic satisfiability (Ssat) problem and solving that problem instead [1]. The values of some of the variables in an Ssat instance are probabilistically determined; APPSSAT considers… (More)
DOI: 10.1007/11518655_19

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