Proceedings

Multi-Armed Bandits for Adaptive Constraint Propagation

Amine Balafrej, Christian Bessière, Anastasia Paparrizou

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 290-295.

Abstract

Adaptive constraint propagation has recently received a great attention. It allows a constraint solver to exploit various levels of propagation during search, and in many cases it shows better performance than static/predefined. The crucial point is to make adaptive constraint propagation automatic, so that no expert knowledge or parameter specification is required. In this work, we propose a simple learning technique, based on multi-armed bandits, that allows to automatically select among several levels of propagation during search. Our technique enables the combination of any number of levels of propagation whereas existing techniques are only defined for pairs. An experimental evaluation demonstrates that the proposed technique results in a more efficient and stable solver.

Amine Balafrej, Christian Bessiere, and Anastasia Paparrizou. 2015. Multi-Armed Bandits for Adaptive Constraint Propagation. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 290–295. https://ijcai.org/proceedings/2015/47
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