A Probabilistic Approach to Satisfiability of Propositional Logic Formulae

TL;DR

BetaWalkSAT introduces a probabilistic biasing method using Beta distribution to improve local search for propositional satisfiability, outperforming traditional uninformed approaches on complex problems.

Contribution

It presents BetaWalkSAT, a novel probabilistic local search algorithm that leverages Beta distribution for better initial state selection in SAT problems.

Findings

BetaWalkSAT outperforms uninformed local search methods.

Probabilistic biasing improves search efficiency.

Effective on complex boolean satisfiability problems.

Abstract

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.