The theory of evolution strategies
The theory of evolution strategies
Noisy Local Optimization with Evolution Strategies
Noisy Local Optimization with Evolution Strategies
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
A Comparison of Evolution Strategies with Other Direct Search Methods in the Presence of Noise
Computational Optimization and Applications
Where Elitists Start Limping Evolution Strategies at Ridge Functions
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Step-Size Adaption Based on Non-Local Use of Selection Information
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
A New Approach for Predicting the Final Outcome of Evolution Strategy Optimization Under Noise
Genetic Programming and Evolvable Machines
Expected sample moments of concomitants of selected order statistics
Statistics and Computing
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Analysis of the (1, λ) - ES on the Parabolic Ridge
Evolutionary Computation
Analysis of the (μ/μ, λ) - ES on the Parabolic Ridge
Evolutionary Computation
Hierarchically organised evolution strategies on the parabolic ridge
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Toward a theory of evolution strategies: On the benefits of sex---the (μ/μ, λ) theory
Evolutionary Computation
Toward a theory of evolution strategies: Self-adaptation
Evolutionary Computation
Self-adaptation on the ridge function class: first results for the sharp ridge
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Optimal weighted recombination
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Evolutionary algorithms and gradient search: similarities anddifferences
IEEE Transactions on Evolutionary Computation
On the performance of (1, λ)-evolution strategies for theridge function class
IEEE Transactions on Evolutionary Computation
Why noise may be good: additive noise on the sharp ridge
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Step length adaptation on ridge functions
Evolutionary Computation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
On the behaviour of evolution strategies optimising cigar functions
Evolutionary Computation
Handling expensive optimization with large noise
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Cumulative step-size adaptation on linear functions
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
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This paper presents an analysis of the performance of the (μ/μ,驴)-ES with isotropically distributed mutations and cumulative step length adaptation on the noisy parabolic ridge. Several forms of dependency of the noise strength on the distance from the ridge axis are considered. Closed form expressions are derived that describe the mutation strength and the progress rate of the strategy in high-dimensional search spaces. It is seen that as for the sphere model, larger levels of noise present lead to cumulative step length adaptation generating increasingly inadequate mutation strengths, and that the problem can be ameliorated to some degree by working with larger populations.