Work

MaxSAT by Improved Instance-Specific Algorithm Configuration

Year: 2014

Type: conference-paper

Abstract: Our objective is to boost the state-of-the-art performance in MaxSATsolving. To this end, we employ the instance-specific algorithmconfigurator ISAC, and improve it with the latest inportfolio technology. Experimental results on SAT show that thiscombination marks a significant step forward in our ability to tunealgorithms instance-specifically. We then apply the new methodology toa number of MaxSAT problem domains and show that the resulting solversconsistently outperform the best existing solvers on the respectiveproblem families. In fact, the solvers presented here were independentlyevaluated at the 2013 MaxSAT Evaluation where they won six of the elevencategories.

Source: Proceedings of the AAAI Conference on Artificial Intelligence

DOI: 10.1609/aaai.v28i1.9128

Authors: Carlos Ansotegui, Yuri Malitsky, Meinolf Sellmann

Institutions: Universitat de Lleida, Insight SFI Research Centre for Data Analytics, IBM (United States), IBM Research - Thomas J. Watson Research Center

Language: English

Topic: Constraint Satisfaction and Optimization

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Science Foundation Ireland, Insight SFI Research Centre for Data Analytics