We implement a weighted negative update of the covariance matrix in the CMA-ES—weighted active CMA-ES or, in short, aCMA-ES. We benchmark the IPOP-aCMA-ES and compare the perfor...
The Covariance-Matrix-Adaptation Evolution-Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD . Recently, ...
The choice of which of the available strategies should be used within the Differential Evolution algorithm for a given problem is not trivial, besides being problem-dependent and...
In this paper, we compare the (1+1)-CMA-ES to the (1+2s m)CMA-ES, a recently introduced quasi-random (1+2)-CMAES that uses mirroring as derandomization technique as well as a sequ...
Sequential selection was introduced for Evolution Strategies (ESs) with the aim of accelerating their convergence— performing the evaluations of the different offspring sequen...