SUNNY for Algorithm Selection: A Preliminary Study

Roberto Amadini 1, 2 Fabio Biselli 1 Maurizio Gabbrielli 2, 1 Tong Liu 1 Jacopo Mauro 2, 1
2 FOCUS - Foundations of Component-based Ubiquitous Systems
CRISAM - Inria Sophia Antipolis - Méditerranée , DISI - Dipartimento di Informatica - Scienza e Ingegneria [Bologna]
Abstract : Given a collection of algorithms, the Algorithm Selection (AS) problem consists in identifying which of them is the best one for solving a given problem. In this paper we show how we adapted the algorithm selector SUNNY, originally tailored for constraint solving, to deal with general AS problems. Preliminary investigations based on the AS Library benchmarks already show some promising results: for some scenarios SUNNY is able to outperform AS state-of-the-art approaches.
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Roberto Amadini, Fabio Biselli, Maurizio Gabbrielli, Tong Liu, Jacopo Mauro. SUNNY for Algorithm Selection: A Preliminary Study. CILC, Jul 2015, Genova, Italy. ⟨hal-01227595⟩

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