Step-Size Adaption Based on Non-Local Use of Selection Information

The performance of Evolution Strategies (ESs) depends on a suitable choice of internal strategy control parameters. Apart from a fixed setting, ESs facilitate an adjustment of such parameters within a self-adaptation process. For step-size control in particular, various adaptation concepts were evolved early in the development of ESs. These algorithms mostly work very efficiently as long as the relative sensitivities of the parameters to be optimized are known. If this scaling is not known, the strategy has to adapt individual step-sizes for the parameters. In general, the number of necessary step-sizes (variances) equals the dimension of the problem. In this case, step-size adaptation proves to be difficult.