Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Toward a theory of evolution strategies: Some asymptotical results from the (1,+ λ)-theory
Evolutionary Computation
Toward a theory of evolution strategies: The (μ, λ)-theory
Evolutionary Computation
Hybrid Evolutionary Search Method Based on Clusters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parameter optimization for visual obstacle detection using a derandomized evolution strategy
Imaging and vision systems
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
Statistical Characteristics of Evolution Strategies
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Efficiency and Mutation Strength Adaptation of the (mu, muI, lambda)-ES in a Noisy Environment
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Evolutionary algorithms in modeling and animation
Handbook of computer animation
Multiparent recombination in evolutionary computing
Advances in evolutionary computing
Information Sciences: an International Journal - Special issue: Evolutionary computation
Basic principles for understanding evolutionary algorithms
Fundamenta Informaticae
An Analysis of Two-Parent Recombinations for Real-Valued Chromosomes in an Infinite Population
Evolutionary Computation
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Self-Adaptive Genetic Algorithms with Simulated Binary Crossover
Evolutionary Computation
Where Genetic Algorithms Excel
Evolutionary Computation
Analysis of the (μ/μ, λ) - ES on the Parabolic Ridge
Evolutionary Computation
Weighted multirecombination evolution strategies
Theoretical Computer Science - Foundations of genetic algorithms
An evolutionary machine learning: An adaptability perspective at fine granularity
International Journal of Knowledge-based and Intelligent Engineering Systems
Toward a theory of evolution strategies: The (μ, λ)-theory
Evolutionary Computation
Toward a theory of evolution strategies: Self-adaptation
Evolutionary Computation
A note on the empirical evaluation of intermediate recombination
Evolutionary Computation
Empirical investigation of multiparent recombination operators in evolution strategies
Evolutionary Computation
Rigorous hitting times for binary mutations
Evolutionary Computation
Lower Bounds for Evolution Strategies Using VC-Dimension
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Evolution strategies with cumulative step length adaptation on the noisy parabolic ridge
Natural Computing: an international journal
On the limitations of adaptive resampling in using the student's t-test evolution strategies
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
How to Do Recombination in Evolution Strategies: An Empirical Study
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Optimal weighted recombination
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Convergence analysis and improvements of quantum-behaved particle swarm optimization
Information Sciences: an International Journal
On some properties of binary chromosomes and states of artificial immune systems
International Journal of Data Analysis Techniques and Strategies
Basic principles for understanding evolutionary algorithms
Fundamenta Informaticae
Finite Markov Chain Results in Evolutionary Computation: A Tour d'Horizon
Fundamenta Informaticae
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The multirecombinant (μ/μ, λ) evolution strategy (ES) is investigated for real-valued, N-dimensional parameter spaces. The analysis includes both intermediate recombination and dominant recombination, as well. These investigations are done for the spherical model first. The problem of the optimal population size depending on the parameter space dimension N is solved. A method extending the results obtained for the spherical model to nonspherical success domains is presented. The power of sexuality is discussed and it is shown that this power does not stem mainly from the “combination” of “good properties” of the mates (building block hypothesis) but rather from genetic repair diminishing the influence of harmful mutations. The dominant recombination is analyzed by introduction of surrogate mutations leading to the concept of species. Conclusions for evolutionary algorithms (EAs), including genetic algorithms (GAs), are drawn.