Quantifier Elimination in Stochastic Boolean Satisfiability

Stochastic Boolean Satisfiability (SSAT) generalizes quantified Boolean formulas (QBFs) by allowing quantification over random variables. Its generality makes SSAT powerful to model decision or optimization problems under uncertainty. On the other hand, the generalization complicates the computation in its counting nature. In this work, we address the following two questions: 1) Is there an analogy of quantifier elimination in SSAT, similar to QBF? 2) If quantifier elimination is possible for SSAT, can it be effective for SSAT solving? We answer them affirmatively, and develop an SSAT decision procedure based on quantifier elimination. Experimental results demonstrate the unique benefits of the new method compared to the state-of-the-art solvers.
LIPIcs, Vol. 236, 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022), pages 23:1-23:17