SUNNY with Algorithm Configuration

Tong Liu, Roberto Amadini, Jacopo Mauro
Proceedings of the Open Algorithm Selection Challenge, PMLR 79:12-14, 2017.

Abstract

The SUNNY algorithm is a portfolio technique originally tailored for Constraint Satisfaction Problems (CSPs). SUNNY allows to select a set of solvers to be run on a given CSP, and was proven to be effective in the MiniZinc Challenge, i.e., the yearly international competition for CP solvers. In 2015, SUNNY was compared with other solver selectors in the first ICON Challenge on algorithm selection with less satisfactory performance. In this paper we briefly describe the new version of the SUNNY approach for algorithm selection, that was submitted to the first Open Algorithm Selection Challenge.

Cite this Paper

BibTeX
@InProceedings{pmlr-v79-liu17a, title = {SUNNY with Algorithm Configuration}, author = {Liu, Tong and Amadini, Roberto and Mauro, Jacopo}, booktitle = {Proceedings of the Open Algorithm Selection Challenge}, pages = {12--14}, year = {2017}, editor = {Lindauer, Marius and van Rijn, Jan N. and Kotthoff, Lars}, volume = {79}, series = {Proceedings of Machine Learning Research}, month = {11--12 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v79/liu17a/liu17a.pdf}, url = {https://proceedings.mlr.press/v79/liu17a.html}, abstract = {The SUNNY algorithm is a portfolio technique originally tailored for Constraint Satisfaction Problems (CSPs). SUNNY allows to select a set of solvers to be run on a given CSP, and was proven to be effective in the MiniZinc Challenge, i.e., the yearly international competition for CP solvers. In 2015, SUNNY was compared with other solver selectors in the first ICON Challenge on algorithm selection with less satisfactory performance. In this paper we briefly describe the new version of the SUNNY approach for algorithm selection, that was submitted to the first Open Algorithm Selection Challenge.} }
Endnote
%0 Conference Paper %T SUNNY with Algorithm Configuration %A Tong Liu %A Roberto Amadini %A Jacopo Mauro %B Proceedings of the Open Algorithm Selection Challenge %C Proceedings of Machine Learning Research %D 2017 %E Marius Lindauer %E Jan N. van Rijn %E Lars Kotthoff %F pmlr-v79-liu17a %I PMLR %P 12--14 %U https://proceedings.mlr.press/v79/liu17a.html %V 79 %X The SUNNY algorithm is a portfolio technique originally tailored for Constraint Satisfaction Problems (CSPs). SUNNY allows to select a set of solvers to be run on a given CSP, and was proven to be effective in the MiniZinc Challenge, i.e., the yearly international competition for CP solvers. In 2015, SUNNY was compared with other solver selectors in the first ICON Challenge on algorithm selection with less satisfactory performance. In this paper we briefly describe the new version of the SUNNY approach for algorithm selection, that was submitted to the first Open Algorithm Selection Challenge.
APA
Liu, T., Amadini, R. & Mauro, J.. (2017). SUNNY with Algorithm Configuration. Proceedings of the Open Algorithm Selection Challenge, in Proceedings of Machine Learning Research 79:12-14 Available from https://proceedings.mlr.press/v79/liu17a.html.

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