Publication Details

The Configurable SAT Solver Challenge (CSSC)

authored by
Frank Hutter, Marius Lindauer, Adrian Balint, Sam Bayless, Holger Hoos, Kevin Leyton-Brown
Abstract

It is well known that different solution strategies work well for different types of instances of hard combinatorial problems. As a consequence, most solvers for the propositional satisfiability problem (SAT) expose parameters that allow them to be customized to a particular family of instances. In the international SAT competition series, these parameters are ignored: solvers are run using a single default parameter setting (supplied by the authors) for all benchmark instances in a given track. While this competition format rewards solvers with robust default settings, it does not reflect the situation faced by a practitioner who only cares about performance on one particular application and can invest some time into tuning solver parameters for this application. The new Configurable SAT Solver Competition (CSSC) compares solvers in this latter setting, scoring each solver by the performance it achieved after a fully automated configuration step. This article describes the CSSC in more detail, and reports the results obtained in its two instantiations so far, CSSC 2013 and 2014.

External Organisation(s)
University of Freiburg
Ulm University
University of British Columbia
Type
Article
Journal
Artificial intelligence
Volume
243
Pages
1-25
No. of pages
25
ISSN
0004-3702
Publication date
02.2017
Publication status
Published
Peer reviewed
Yes
ASJC Scopus subject areas
Language and Linguistics, Linguistics and Language, Artificial Intelligence
Electronic version(s)
https://arxiv.org/abs/1505.01221 (Access: Open)
https://doi.org/10.1016/j.artint.2016.09.006 (Access: Open)