Self-Adaptation of Multirecombinant Evolution Strategies on the Highly Multimodal Rastrigin Function
研究了自适应的多重组进化策略在高度多峰的Rastrigin测试函数上的表现，通过理论推导和实验验证了学习参数τ的调节方法，并与默认值比较，发现理论预测与实验吻合良好。
The self-adaptive, multi-recombinative (μ/μI,λ)-ES (Evolution Strategy) is investigated on the highly multimodal Rastrigin test function by theoretical and experimental means. The analysis is based on the established dynamical systems approach. To this end, the self-adaptation response function is derived in the limit of large populations, which are necessary to achieve high success rates. Furthermore, steady-state conditions on Rastrigin are discussed and compared to the sphere function. Then, a relation for the learning parameter τ is derived to tune the sampling process of the self-adaptive ES, improving its efficiency on Rastrigin. The obtained result is compared to default τ-values. Furthermore, expected runtime experiments are conducted varying τ and population parameters of the ES. Theoretical and experimental results regarding τ are compared in terms of efficiency and robustness showing good agreement.