Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Optimal Mutation Rates in Genetic Search
Proceedings of the 5th International Conference on Genetic Algorithms
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Multimodal Performance Profiles on the Adaptive Distributed Database Management Problem
Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
The Advantages of Landscape Neutrality in Digital Circuit Evolution
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
GA-Based Learning of kDNFns Boolean Formulas
ICES '01 Proceedings of the 4th International Conference on Evolvable Systems: From Biology to Hardware
Human evolutionary model: A new approach to optimization
Information Sciences: an International Journal
Genetic algorithms, selection schemes, and the varying effects of noise
Evolutionary Computation
Analysis of selection algorithms: A markov chain approach
Evolutionary Computation
Evolutionary induction of sparse neural trees
Evolutionary Computation
The equation for response to selection and its use for prediction
Evolutionary Computation
Optimization of road networks using evolutionary strategies
Evolutionary Computation
The gambler's ruin problem, genetic algorithms, and the sizing of populations
Evolutionary Computation
Scalability problems of simple genetic algorithms
Evolutionary Computation
Fda -a scalable evolutionary algorithm for the optimization of additively decomposed functions
Evolutionary Computation
An analysis of the “universal suffrage” selection operator
Evolutionary Computation
Journal of Global Optimization
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
EDNA: Estimation of Dependency Networks Algorithm
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
The evolutionary learning rule for system identification
Applied Soft Computing
Searching under multi-evolutionary pressures
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
A diversity preserving selection in multiobjective evolutionary algorithms
Applied Intelligence
Optimizing a new nonlinear reinforcement scheme with Breeder genetic algorithm
NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
Generic reinforcement schemes and their optimization
ECC'11 Proceedings of the 5th European conference on European computing conference
Theory and practice of cellular UMDA for discrete optimization
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Evolutionary generation of prototypes for a learning vector quantization classifier
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Fluctuating crosstalk as a source of deterministic noise and its effects on GA scalability
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
The allele meta-model – developing a common language for genetic algorithms
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Selection Mechanisms in Evolutionary Algorithms
Fundamenta Informaticae
Finite Markov Chain Results in Evolutionary Computation: A Tour d'Horizon
Fundamenta Informaticae
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The breeder genetic algorithm (BGA) models artificial selection as performed by human breeders. The science of breeding is based on advanced statistical methods. In this paper a connection between genetic algorithm theory and the science of breeding is made. We show how the response to selection equation and the concept of heritability can be applied to predict the behavior of the BGA. Selection, recombination, and mutation are analyzed within this framework. It is shown that recombination and mutation are complementary search operators. The theoretical results are obtained under the assumption of additive gene effects. For general fitness landscapes, regression techniques for estimating the heritability are used to analyze and control the BGA. The method of decomposing the genetic variance into an additive and a nonadditive part connects the case of additive fitness functions with the general case.