Machine Learning-Based Restart Policy for CDCL SAT Solvers

Jia Hui Liang
Jia Hui Liang
Chanseok Oh
Chanseok Oh
Minu Mathew
Minu Mathew

SAT, pp. 94-110, 2018.

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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Restarts are a critically important heuristic in most modern conflict-driven clause-learning (CDCL) SAT solvers. The precise reason as to why and how restarts enable CDCL solvers to scale efficiently remains obscure. In this paper we address this question, and provide some answers that enabled us to design a new effective machine learning...More

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