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Titlebook: Linkage in Evolutionary Computation; Ying-ping Chen,Meng-Hiot Lim Book 2008 Springer-Verlag Berlin Heidelberg 2008 Bayesian network.Evolut

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Linkage Learning Accuracy in the Bayesian Optimization Algorithmpter studies the influence of different selection and replacement methods on the accuracy of linkage learning in BOA. Results on concatenated m-k deceptive trap functions show that the model accuracy depends on a large extent on the choice of selection method and to a lesser extent on the replacemen
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Parallel GEAs with Linkage Analysis over Gridlgorithms (GEAs) especially linkage based GEAs. We concentrate mainly on the Grid computing paradigm which is widely accepted as the most distributed form of computing; due to the advent of Service Oriented Architecture (SOA) and other technologies, Grid has gained a lot of attention in the recent y
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A Clustering-Based Approach for Linkage Learning Applied to Multimodal Optimizationres present in the problem being solved. Similarities are currently taken into account in evolutionary computation since the preservation of the diversity in the population is considered very important to allow the identification of the problem structure, as much as to find and maintain several glob
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EpiSwarm, a Swarm-Based System for Investigating Genetic Epistasisto different disease outcomes. Due to the nonlinear interactions among the genes, data such as this is difficult to model using traditional epidemiological tools. Thus, we have developed EpiSwarm, a Swarm-based system for investigating complex genetic diseases. EpiSwarm uses genetic algorithms evolu
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Real-Coded Extended Compact Genetic Algorithm Based on Mixtures of ModelsBayesian Optimization Algorithm (rBOA). Like ECGA, the proposed algorithm partitions the problem variables into a set of clusters that are manipulated as independent variables and estimates the population distribution using marginal product models (MPMs); like rBOA, it employs finite mixtures of mod
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