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GECCO
2010
Springer

Fitness-AUC bandit adaptive strategy selection vs. the probability matching one within differential evolution: an empirical comp

9 years 4 months ago
Fitness-AUC bandit adaptive strategy selection vs. the probability matching one within differential evolution: an empirical comp
The choice of which of the available strategies should be used within the Differential Evolution algorithm for a given problem is not trivial, besides being problem-dependent and very sensitive with relation to the algorithm performance. This decision can be made in an autonomous way, by the use of the Adaptive Strategy Selection paradigm, that continuously selects which strategy should be used for the next offspring generation, based on the performance achieved by each of the available ones on the current optimization process, i.e., while solving the problem. In this paper, we use the BBOB-2010 noiseless benchmarking suite to better empirically validate a comparison-based technique recently proposed to do so, the Fitness-based Area-Under-Curve Bandit [4], referred to as F-AUC-Bandit. It is compared with another recently proposed approach that uses Probability Matching technique based on the relative fitness improvements, referred to as PM-AdapSS-DE [7]. Categories and Subject Desc...
Álvaro Fialho, Marc Schoenauer, Michè
Added 19 Jul 2010
Updated 19 Jul 2010
Type Conference
Year 2010
Where GECCO
Authors Álvaro Fialho, Marc Schoenauer, Michèle Sebag
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