Simple algorithm portfolio for SAT

Authors:
Mladen Nikolić;Filip Marić;Predrag Janiăčić
Affiliations:
Faculty of Mathematics, University of Blegrade, Belgrade, Serbia;Faculty of Mathematics, University of Blegrade, Belgrade, Serbia;Faculty of Mathematics, University of Blegrade, Belgrade, Serbia
Venue:
Artificial Intelligence Review
Year:
2013

Citing 11
Cited 0

Algorithm portfolios

Artificial Intelligence - special issue on computational tradeoffs under bounded resources
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Formalization and Implementation of Modern SAT Solvers

Journal of Automated Reasoning
Instance-Based Selection of Policies for SAT Solvers

SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Learning to solve QBF

AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
SATzilla: portfolio-based algorithm selection for SAT

Journal of Artificial Intelligence Research
ParamILS: an automatic algorithm configuration framework

Journal of Artificial Intelligence Research
A gender-based genetic algorithm for the automatic configuration of algorithms

CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
ISAC --Instance-Specific Algorithm Configuration

Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Non-model-based algorithm portfolios for SAT

SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
A bayesian approach to tackling hard computational problems

UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

The importance of algorithm portfolio techniques for SAT has long been noted, and a number of very successful systems have been devised, including the most successful one--SATzilla. However, all these systems are quite complex (to understand, reimplement, or modify). In this paper we present an algorithm portfolio for SAT that is extremely simple, but in the same time so efficient that it outperforms SATzilla. For a new SAT instance to be solved, our portfolio finds its k-nearest neighbors from the training set and invokes a solver that performs the best for those instances. The main distinguishing feature of our algorithm portfolio is the locality of the selection procedure--the selection of a SAT solver is based only on few instances similar to the input one. An open source tool that implements our approach is publicly available.