This work presents theoretical results on the development of a statistical convergence criterion for evolutionary algorithms. An analytical formula is derived for the probability of success in isotropic Gaussian mutation operators over spherical functions, and statistical criteria are proposed for evaluating, with predefined confidence levels, the convergence of (1+1) and (1+λ) Evolution Strategies. The results presented are intended as a first approach to the development of statistically based stop criteria for evolutionary optimizers, and as a contribution for the broader application of statistical modeling to the development and study of population-based algorithms.
|Title of host publication||Proceedings of the 2015 Latin America Congress on Computational Intelligence (LA-CCI)|
|Publication status||Published - 21 Mar 2016|
|Event||2015 Latin America Congress on Computational Intelligence (LA-CCI) - Curitiba, Brazil|
Duration: 13 Oct 2015 → 16 Oct 2015
|Conference||2015 Latin America Congress on Computational Intelligence (LA-CCI)|
|Period||13/10/15 → 16/10/15|
Campelo, F. (2016). Towards statistical convergence criteria for mutation-based evolutionary algorithms. In Proceedings of the 2015 Latin America Congress on Computational Intelligence (LA-CCI) IEEE. https://doi.org/10.1109/la-cci.2015.7435944