Policy Gradient MaxSAT Solver

Omar Gutiérrez-De-La-Paz, Ricardo Menchaca-Méndez, Erik Zamora-Gómez, Uriel Corona-Bermudez, Rolando Menchaca-Méndez, Bruno Gutiérrez-De-La-Paz

Abstract


This paper presents a comparative study of various elements and strategies that can be incorporated into an autoregressive model to address the MaxSAT problem. Building upon a sequential architecture as our foundation, we optimize the model's parameters by maximizing the expected number of satisfied clauses. This optimization enables the model, given a SAT formula, to predict a distribution over potential solutions using the policy gradient method. Our controlled experiments pinpoint elements that guide the optimization process towards superior results.

Keywords


MaxSAT Problem; Policy Gradient; NP-Hard

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