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Section: Software

Keywords : Evolutionary Computation, stochastic optimization, real-parameter optimization.

Covariance Matrix Adaptation Evolution Strategy

Participant : Nikolaus Hansen [ correspondent ] .

The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is one of the most powerful continuous domain evolutionary algorithms. The CMA-ES is considered state-of-the-art in continuous domain evolutionary computation (H.-G. Beyer (2007). Evolution Strategies, Scholarpedia , p. 1965)and has been shown to be highly competitive on different problem classes. The algorithm is widely used in research and industry as witnessed by more than a hundred published applications. We provide source code for the CMA-ES in C, Java, Matlab, Octave, Python, and Scilab including the latest variants of the algorithm [27] .

Links: http://www.lri.fr/~hansen/cmaes_inmatlab.html


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