2014/02/18 by Peter van der Tak, Marijn J. H. Heule, van der Tak, Peter +3
Computer Science · #Artificial Intelligence (cs.AI) #Constraint Satisfaction and Optimization #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Formal Methods in Verification #Logic, programming, and type systems #cs.AI #cs.DS
paper · pdf · doi:10.48550/arxiv.1402.4465
Third International Workshop on Pragmatics of SAT (PoS 2012)
arxiv created 2014/02/18 · openalex publication_date 2014/02/18 · arxiv updated 2014/02/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recent work introduced the cube-and-conquer technique to solve hard SAT instances. It partitions the search space into cubes using a lookahead solver. Each cube is tackled by a conflict-driven clause learning (CDCL) solver. Crucial for strong performance is the cutoff heuristic that decides when to switch from lookahead to CDCL. Yet, this offline heuristic is far from ideal. In this paper, we present a novel hybrid solver that applies the cube and conquer steps simultaneously. A lookahead and a CDCL solver work together on each cube, while communication is restricted to synchronization. Our concurrent cube-and-conquer solver can solve many instances faster than pure lookahead, pure CDCL and offline cube-and-conquer, and can abort early in favor of a pure CDCL search if an instance is not suitable for cube-and-conquer techniques.