Convergence in evolutionary programs with self-adaptation

Evolutionary programs are capable of �nding good solutions to dif�cult optimization problems. Previous analysis of their convergence properties has normally assumed the strategy parameters are kept constant, although in practice these parameters are dynamically altered. In this paper, we propose a modi�ed version of the 1/5-success rule for self-adaptation in evolution strategies (ES). Formal proofs of the long-term behavior produced by our self-adaptation method are included. Both elitist and nonelitist ES variants are analyzed. Preliminary tests indicate an ES with our modi�ed selfadaptation method compares favorably to both a non-adapted ES and a 1/5-success rule adapted ES