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Weighted multirecombination evolution strategies
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Optimum tracking with evolution strategies
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On the use of evolution strategies for optimising certain positive definite quadratic forms
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Analysis of noisy time-series signals with GA involving viral infection with tropism
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Why noise may be good: additive noise on the sharp ridge
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Theoretical analysis of genetic algorithms in noisy environments based on a Markov Model
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Step length adaptation on ridge functions
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On Multiplicative Noise Models for Stochastic Search
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Uncertainty Handling in Model Selection for Support Vector Machines
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Evolution strategies with cumulative step length adaptation on the noisy parabolic ridge
Natural Computing: an international journal
Weighted recombination evolution strategy on a class of PDQF's
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Ordinal Optimization and Quantification of Heuristic Designs
Discrete Event Dynamic Systems
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Markov chain analysis of genetic algorithms in a wide variety of noisy environments
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Uncertainty handling CMA-ES for reinforcement learning
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Neuroevolution strategies for episodic reinforcement learning
Journal of Algorithms
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
CEC'09 Proceedings of the Eleventh conference on Congress 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
The steady state behavior of (µ/µI, λ)-ES on ellipsoidal fitness models disturbed by noise
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Selection in the presence of noise
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Cumulative step length adaptation for evolution strategies using negative recombination weights
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Parameter evolution: a design pattern for active vision
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
On the analysis of self-adaptive evolution strategies on elliptic model: first results
Proceedings of the 12th annual conference on Genetic and evolutionary computation
On the behaviour of evolution strategies optimising cigar functions
Evolutionary Computation
On the behaviour of the (1,λ)-es for a simple constrained problem
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Analysis of a repair mechanism for the (1,λ)-ES applied to a simple constrained problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
The effects of selection on noisy fitness optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
How comma selection helps with the escape from local optima
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Multi-objective optimization of problems with epistemic uncertainty
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Optimal weighted recombination
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
On the prediction of the solution quality in noisy optimization
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Computational Optimization and Applications
Quantum control experiments as a testbed for evolutionary multi-objective algorithms
Genetic Programming and Evolvable Machines
Optimal computing budget allocation for small computing budgets
Proceedings of the Winter Simulation Conference
Controlling population size and mutation strength by Meta-ES under fitness noise
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
On the behaviour of the (1, λ)-es for a conically constrained problem
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Resampling versus repair in evolution strategies applied to a constrained linear problem
Evolutionary Computation
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From the Publisher:"Noisy Optimization With Evolution Strategies contributes the understanding of evolutionary optimization in the presence of noise by investigating the performance of evolution strategies, a type of evolutionary algorithm frequently employed for solving real-valued optimization problems." Noisy Optimization With Evolution Strategies is an invaluable resource for researchers and practitioners of evolutionary algorithms.