Nagging: a scalable fault-tolerant paradigm for distributed search
Artificial Intelligence
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Guiding Real-World SAT Solving with Dynamic Hypergraph Separator Decomposition
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Learning dynamic algorithm portfolios
Annals of Mathematics and Artificial Intelligence
Low-knowledge algorithm control
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Combining multiple heuristics online
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Restart schedules for ensembles of problem instances
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
Experiments with massively parallel constraint solving
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A collaborative approach for multi-threaded SAT solving
International Journal of Parallel Programming
ParamILS: an automatic algorithm configuration framework
Journal of Artificial Intelligence Research
SATzilla-07: the design and analysis of an algorithm portfolio for SAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
JaCk-SAT: a new parallel scheme to solve the satisfiability problem (SAT) based on join-and-check
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Algorithm selection and scheduling
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
A bayesian approach to tackling hard computational problems
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Algorithm portfolio design: theory vs. practice
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Using CBR to select solution strategies in constraint programming
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Parallel SAT solver selection and scheduling
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
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Portfolio-based solvers are both effective and robust, but their promise for parallel execution with constraint satisfaction solvers has received relatively little attention. This paper proposes an approach that constructs algorithm portfolios intended for parallel execution based on a combination of case-based reasoning, a greedy algorithm, and three heuristics. Empirical results show that this method is efficient, and can significantly improve performance with only a few additional processors. On problems from solver competitions, the resultant algorithm portfolios perform nearly as well as an oracle.