Algorithm portfolios try to combine the strength of individual algorithms to tackle a problem instance at hand with the most suitable technique. In the context of SAT the effectiveness of such approaches is often demonstrated at the SAT Competitions. In this paper we show that a competitive algorithm portfolio can be designed in an extremely simple fashion. In fact, the algorithm portfolio we present does not require any offline learning nor knowledge of any complex Machine Learning tools. We hope that the utter simplicity of our approach combined with its effectiveness will make algorithm portfolios accessible by a broader range of researchers including SAT and CSP solver developers. © 2013 Springer-Verlag.
CITATION STYLE
Samulowitz, H., Reddy, C., Sabharwal, A., & Sellmann, M. (2013). Snappy: A simple algorithm portfolio. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7962 LNCS, pp. 422–428). https://doi.org/10.1007/978-3-642-39071-5_33
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