Fitness-AUC Bandit Adaptive Strategy Selection vs. the Probability Matching one within Differential Evolution: An Empirical Comparison on the BBOB-2010 Noiseless Testbed

Álvaro Fialho 1 Marc Schoenauer 1, 2, 3 Michèle Sebag 1, 2, 3
2 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : 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, 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.
Type de document :
Communication dans un congrès
GECCO 2010 Workshop on Black-Box Optimization Benchmarking, Jul 2010, Portland, United States. 2010
Liste complète des métadonnées

Littérature citée [2 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00494535
Contributeur : Álvaro Fialho <>
Soumis le : dimanche 11 juillet 2010 - 02:12:52
Dernière modification le : jeudi 5 avril 2018 - 12:30:12
Document(s) archivé(s) le : mardi 12 octobre 2010 - 10:06:15

Identifiants

  • HAL Id : inria-00494535, version 2

Collections

Citation

Álvaro Fialho, Marc Schoenauer, Michèle Sebag. Fitness-AUC Bandit Adaptive Strategy Selection vs. the Probability Matching one within Differential Evolution: An Empirical Comparison on the BBOB-2010 Noiseless Testbed. GECCO 2010 Workshop on Black-Box Optimization Benchmarking, Jul 2010, Portland, United States. 2010. 〈inria-00494535v2〉

Partager

Métriques

Consultations de la notice

332

Téléchargements de fichiers

1024