Why noise may be good: additive noise on the sharp ridge
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Evolutionary optimization of dynamics models in sequential Monte Carlo target tracking
IEEE Transactions on Evolutionary Computation
Mutative self-adaptation on the sharp and parabolic ridge
FOGA'07 Proceedings of the 9th international conference on Foundations of genetic algorithms
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This paper investigates the self-adaptation behavior of ( $$1,\lambda $$)-evolution strategies (ES) on the noisy sphere model. To this end, the stochastic system dynamics is approximated on the level of the mean value dynamics. Being based on this "microscopic" analysis, the steady state behavior of the ES for the scaled noise scenario and the constant noise strength scenario will be theoretically analyzed and compared with real ES runs. An explanation will be given for the random walk like behavior of the mutation strength in the vicinity of the steady state. It will be shown that this is a peculiarity of the $$(1,\lambda)$$-ES and that intermediate recombination strategies do not suffer from such behavior.