DCMA, yet another derandomization in covariance-matrix-adaptation - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2007

DCMA, yet another derandomization in covariance-matrix-adaptation


In a preliminary part of this paper, we analyze the neces- sity of randomness in evolution strategies. We conclude to the necessity of ”continuous”-randomness, but with a much more limited use of randomness than what is commonly used in evolution strategies. We then apply these results to CMA- ES, a famous evolution strategy already based on the idea of derandomization, which uses random independent Gaus- sian mutations. We here replace these random independent Gaussian mutations by a quasi-random sample. The mod- ification is very easy to do, the modified algorithm is com- putationally more efficient and its convergence is faster in terms of the number of iterates for a given precision.
Fichier principal
Vignette du fichier
geccodcma.pdf (223.46 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

inria-00173207 , version 1 (19-09-2007)


  • HAL Id : inria-00173207 , version 1


Olivier Teytaud, Sylvain Gelly. DCMA, yet another derandomization in covariance-matrix-adaptation. GECCO, 2007, London, United Kingdom. ⟨inria-00173207⟩
114 View
132 Download


Gmail Facebook X LinkedIn More