Project Team Tao

Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Partnerships and Cooperations
PDF e-pub XML

Section: Software

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, page 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 hundreds of 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.