This paper reviews the recent literature on solving the Boolean satisfiability problem (SAT),
an archetypal NP-complete problem, with the aid of machine learning (ML) techniques. Over …

Original and learnt clauses in Conflict-Driven Clause Learning (CDCL) SAT solvers often
contain redundant literals. This may have a negative impact on solver performance, because …

Improving cdcl via local search Page 43 Improving CDCL via Local Search **ndi Zhang,
Shaowei Cai*, Zhihan Chen 1State Key Laboratory of Computer Science, Institute of Software …

The satisfiability problem (SAT) is a critically important issue in multiple branches of
computer science and artificial intelligence, with its relevance in industrial applications being …

In this paper, we present a Bayesian Moment Matching (BMM) based method aimed at
solving the initialization problem in Boolean SAT solvers. The initialization problem can be …

Boolean satisfiability (SAT) is a propositional logic problem of determining whether an
assignment of variables satisfies a Boolean formula. Many combinatorial optimization …

Abstract Multi-Objective Combinatorial Optimization (MOCO), which consists of several
conflicting objectives to be optimized, finds an ever-increasing number of uses in many real …

Over the last two decades, we have seen a dramatic improvement in the efficiency of conflict-
driven clause-learning Boolean satisfiability (CDCL SAT) solvers over industrial problems …

The SAT-based reduction methods have shown significant effectiveness in solving preferred
extensions problem in argumentation frameworks. As a general-purpose solver, SAT solvers …

Variable elimination is arguably the most important pre-and in-processing technique in state-
of-the-art SAT solvers. There are hardly any problems for which variable elimination by …