CMA-ES with Two-Point Step-Size Adaptation

Nikolaus Hansen 1, 2, *
* Auteur correspondant
1 TANC - Algorithmic number theory for cryptology
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], Inria Saclay - Ile de France, X - École polytechnique, CNRS - Centre National de la Recherche Scientifique : UMR7161
Abstract : We combine a refined version of two-point step-size adaptation with the covariance matrix adaptation evolution strategy (CMA-ES). Additionally, we suggest polished formulae for the learning rate of the covariance matrix and the recombination weights. In contrast to cumulative step-size adaptation or to the 1/5-th success rule, the refined two-point adaptation (TPA) does not rely on any internal model of optimality. In contrast to conventional self-adaptation, the TPA will achieve a better target step-size in particular with large populations. The disadvantage of TPA is that it relies on two additional objective function evaluations.
Type de document :
Rapport
[Research Report] RR-6527, INRIA. 2008
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https://hal.inria.fr/inria-00276854
Contributeur : Nikolaus Hansen <>
Soumis le : dimanche 18 mai 2008 - 01:12:24
Dernière modification le : jeudi 10 mai 2018 - 02:06:18
Document(s) archivé(s) le : vendredi 24 septembre 2010 - 12:12:34

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twopointSA.pdf
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  • HAL Id : inria-00276854, version 5
  • ARXIV : 0805.0231

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Nikolaus Hansen. CMA-ES with Two-Point Step-Size Adaptation. [Research Report] RR-6527, INRIA. 2008. 〈inria-00276854v5〉

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