Simple Surrogate Model Assisted Optimization with Covariance Matrix Adaptation

We aim to observe differences between surrogate model assisted covariance matrix adaptation evolution strategies applied to simple test problems. We propose a simple Gaussian process assisted strategy as a baseline. The performance of the algorithm is compared with those of several related strategies using families of parameterized, unimodal test problems. The impact of algorithm design choices on the observed differences is discussed.