CMA-ES with Two-Point Step-Size Adaptation

Nikolaus Hansen 1, 2
1 TANC - Algorithmic number theory for cryptology
Inria Saclay - Ile de France, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
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
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Contributor : Nikolaus Hansen <>
Submitted on : Friday, May 2, 2008 - 3:53:48 PM
Last modification on : Wednesday, March 27, 2019 - 4:41:29 PM
Long-term archiving on : Tuesday, September 21, 2010 - 4:22:03 PM


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  • HAL Id : inria-00276854, version 2
  • ARXIV : 0805.0231


Nikolaus Hansen. CMA-ES with Two-Point Step-Size Adaptation. [Research Report] 2008. ⟨inria-00276854v2⟩



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