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Improvements to SAT-Based Conformant Planning

Planning as satisfiability is an efficient technique for classical planning. In previous work by the second author, this approach has been extended to conformant planning, that is, to planning domains having incomplete information about the initial state and/or the effects of actions. In this paper we present some domain independent optimizations to the basic procedure described in the previous work. A comparative experimental analysis shows that the resulting procedure is competitive with other state-of-the-art conformant planners on domains with a high degree of parallelism.