The theory of evolution strategies
The theory of evolution strategies
Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
Noisy Local Optimization with Evolution Strategies
Noisy Local Optimization with Evolution Strategies
A Comparison of Evolution Strategies with Other Direct Search Methods in the Presence of Noise
Computational Optimization and Applications
Qualms regarding the optimality of cumulative path length control in CSA/CMA-evolution strategies
Evolutionary Computation
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Toward a theory of evolution strategies: Some asymptotical results from the (1,+ λ)-theory
Evolutionary Computation
A derandomized approach to self-adaptation of evolution strategies
Evolutionary Computation
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Genetic algorithms with a robust solution searching scheme
IEEE Transactions on Evolutionary Computation
Robust design of multilayer optical coatings by means ofevolutionary algorithms
IEEE Transactions on Evolutionary Computation
On self-adaptive features in real-parameter evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Genetic Programming and Evolvable Machines
A New Approach for Predicting the Final Outcome of Evolution Strategy Optimization Under Noise
Genetic Programming and Evolvable Machines
On the use of evolution strategies for optimising certain positive definite quadratic forms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Mutative self-adaptation on the sharp and parabolic ridge
FOGA'07 Proceedings of the 9th international conference on Foundations of genetic algorithms
Theoretical Computer Science
On the prediction of the solution quality in noisy optimization
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
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The method of differential-geometry is applied for deriving steady state conditions for the (µ/µI, 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.