A new approach for predicting the final outcome of evolution strategy optimization under noise
Genetic Programming and Evolvable Machines, 2005•Springer
Differential-geometric methods are applied to derive steady state conditions for the (μ/μ I, λ)-
ES on the general quadratic test function disturbed by fitness noise of constant strength. A
new approach for estimating the expected final fitness deviation observed under such
conditions is presented. The theoretical results obtained are compared with real ES runs,
showing a surprisingly excellent agreement.
ES on the general quadratic test function disturbed by fitness noise of constant strength. A
new approach for estimating the expected final fitness deviation observed under such
conditions is presented. The theoretical results obtained are compared with real ES runs,
showing a surprisingly excellent agreement.
Abstract
Differential-geometric methods are applied to derive steady state conditions for the (μ/μ I ,λ)-ES on the general quadratic test function disturbed by fitness noise of constant strength. A new approach for estimating the expected final fitness deviation observed under such conditions is presented. The theoretical results obtained are compared with real ES runs, showing a surprisingly excellent agreement.
Springer
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