SUNNY for algorithm selection: A preliminary study
R Amadini, F Biselli, M Gabbrielli, T Liu, J Mauro
CEUR Workshop Proceedings | CEUR Workshop Proceedings | Published : 2015
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-ofthe-art approaches.