Algorithm configuration data mining for CMA evolution strategies
Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck · Proceedings of the Genetic and Evolutionary Computation Conference · 2017
In the past years, quite a number of algorithmic extensions of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) have been proposed. These extensions define a large algorithm design space, but relatively little is known about the performance of most of these variations and the interaction between them.