Translation to Boolean satisfiability is an important approach for solving state-space reachability problems that arise in planning and verification. Many important problems, however, involve numeric variables; for example, C programs or planning with resources. Focussing on planning, we propose a method for translating such problems into propositional SAT, based on an approximation of reachable variable domains. We compare to a more direct translation into "SAT modulo theory" (SMT), that is, SAT extended with numeric variables and arithmetic constraints. Though translation to SAT generates much larger formulas, we show that it typically outperforms translation to SMT almost up to the point where the formulas ' don't fit into memory any longer. We also show that, even though our planner is optimal, it tends to outperform state-of-the-art sub-optimal heuristic planners in domains with tightly constrained resources. Finally we present encouraging initial results on applying the approach to model checking.
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