Keywords: Denoising Diffusion, Boolean Satisfiability Problem, Multinomial Diffusion
TL;DR: We use Discrete Denoising Diffusion to sample diverse solutions to the Boolean Satisfiability Problem.
Abstract: Generating diverse solutions to the Boolean Satisfiability Problem (SAT) is a hard computational problem with practical applications for testing and functional verification of software and hardware designs. We explore the way to generate such solutions using Denoising Diffusion coupled with a Graph Neural Network to implement the denoising function. We find that the obtained accuracy is similar to the currently best purely neural method and the produced SAT solutions are highly diverse, even if the system is trained with non-random solutions from a standard solver.
Student Paper: No
Community Implementations: [![CatalyzeX](/images/catalyzex_icon.svg) 2 code implementations](https://www.catalyzex.com/paper/arxiv:2212.00121/code)