Local Performance of the (1 + 1)-ES in a Noisy Environment

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Date

2001-10-16

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Universität Dortmund

Abstract

While noise is a phenomenon present in many real-world optimization problems, the understanding of its potential effects on the performance of evolutionary algorithms is still incomplete. This paper investigates the effects of noise for the infinite-dimensional quadratic sphere and a (1 +1)-ES with isotropic normal mutations. It is shown that overvaluation as a result of failure to reevaluate parental fitness leads to both reduced success probabilities and improved performance. Implications for mutation strength adaptation rules are discussed and optimal resampling rates are computed.

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Keywords

evolution strategy, local performance, noise, overvaluation

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