Policy Gradient MaxSAT Solver

Authors

  • Omar Gutiérrez-De-La-Paz Centro de Investigación en Computación - Instituto Politécnico Nacional
  • Ricardo Menchaca-Méndez Centro de Investigación en Computación - Instituto Politécnico Nacional
  • Erik Zamora-Gómez Centro de Investigación en Computación - Instituto Politécnico Nacional
  • Uriel Corona-Bermudez Centro de Investigación en Computación - Instituto Politécnico Nacional
  • Rolando Menchaca-Méndez Centro de Investigación en Computación - Instituto Politécnico Nacional
  • Bruno Gutiérrez-De-La-Paz Centro de Investigación en Computación - Instituto Politécnico Nacional

DOI:

https://doi.org/10.13053/cys-28-2-4723

Keywords:

MaxSAT Problem, Policy Gradient, NP-Hard

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.

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Published

2024-06-12

Issue

Vol. 28 No. 2 (2024): 28(2) 2024

Section

Articles

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