Improvements to propositional satisfiability search algorithms
Improvements to propositional satisfiability search algorithms
A constraint-based approach to narrow search trees for satisfiability
Information Processing Letters
A machine program for theorem-proving
Communications of the ACM
Annals of Mathematics and Artificial Intelligence
Heuristics based on unit propagation for satisfiability problems
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Present and Future of Practical SAT Solving
Complexity of Constraints
A Novel Approach to Combine a SLS- and a DPLL-Solver for the Satisfiability Problem
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Building a Hybrid SAT Solver via Conflict-Driven, Look-Ahead and XOR Reasoning Techniques
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
| Hi-index | 0.00 |
We introduce an adaptive algorithm to control the use of the double look-ahead procedure. This procedure sometimes enhances the performance of look-ahead based satisfiability solvers. Current use of this procedure is driven by static heuristics. Experiments show that over a wide variety of instances, different parameter settings result in optimal performance. Moreover, a strategy that yields fast performance on one particular class of instances may cause a significant slowdown on other families. Using a single adaptive strategy, we accomplish performances close to the optimal performances reached by the various static settings. On some families, we clearly outperform even the fastest performance based on static heuristics. This paper provides a description of the algorithm and a comparison with the static strategies. This method is incorporated in march_dl, satz, and kcnfs. Also, the dynamic behavior of the algorithm is illustrated by adaptation plots on various benchmarks.