Learning variable activity initialisation for lazy clause generation solvers

DOI10.1007/978-3-030-78230-6_4OpenAlexW3170772251MaRDI QIDQ2117201

Ronald van Driel, Emir Demirović, Neil Yorke-Smith

Publication date: 21 March 2022

Full work available at URL: https://doi.org/10.1007/978-3-030-78230-6_4

Mathematics Subject Classification ID

Combinatorial optimization (90C27) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Uses Software

• Chaff
• GitHub
• CHUFFED
• sunny-cp
• CrystalBall
• NeuroSAT

Cites Work

• Model agnostic solution of CSPs via deep learning: a preliminary study
• Debugging unsatisfiable constraint models
• Machine learning for combinatorial optimization: a methodological tour d'horizon
• Guiding high-performance SAT solvers with unsat-core predictions
• CrystalBall: gazing in the black box of SAT solving
• Propagation via lazy clause generation
• Core-boosted linear search for incomplete MaxSAT
• An investigation into prediction + optimisation for the knapsack problem

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