GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Efficient conflict driven learning in a boolean satisfiability solver
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Present and Future of Practical SAT Solving
Complexity of Constraints
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
A new clause learning scheme for efficient unsatisfiability proofs
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
On Modern Clause-Learning Satisfiability Solvers
Journal of Automated Reasoning
Conflict-driven answer set solving: From theory to practice
Artificial Intelligence
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We show that modern conflict-driven SAT solvers implicitly build and prune a decision tree whose nodes are associated with flipped variables. Practical usefulness of conflict-driven learning schemes, like 1UIP or AllUIP, depends on their ability to guide the solver towards refutations associated with compact decision trees. We propose an enhancement of 1UIP that is empirically helpful for real-world industrial benchmarks.