A Probabilistic Approach to Satisfiability of Propositional Logic Formulae
This work addresses boolean satisfiability problems, which are fundamental in computer science, but it appears incremental as it builds on existing WalkSAT methods.
The authors tackled the problem of solving complex boolean satisfiability by proposing BetaWalkSAT, a variant of WalkSAT that uses probabilistic reasoning and Beta distribution to bias the starting state, resulting in performance improvements over other uninformed local search approaches.
We propose a version of WalkSAT algorithm, named as BetaWalkSAT. This method uses probabilistic reasoning for biasing the starting state of the local search algorithm. Beta distribution is used to model the belief over boolean values of the literals. Our results suggest that, the proposed BetaWalkSAT algorithm can outperform other uninformed local search approaches for complex boolean satisfiability problems.