Titlebook: Estimation of Distribution Algorithms; A New Tool for Evolu Pedro Larrañaga,Jose A. Lozano Book 2002 Springer Science+Business Media New Yo

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A Review on Estimation of Distribution Algorithms in continuous domains. Different approaches for Estimation of Distribution Algorithms have been ordered by the complexity of the interrelations that they are able to express. These will be introduced using one unified notation.

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Mathematical Modeling of Discrete Estimation of Distribution Algorithmsrature by introducing them into two general frameworks: Markov chains and dynamical systems. In addition, we use Markov chains to give a general convergence result for discrete EDAs. Some discrete EDAs are analyzed using this result, to obtain sufficient conditions for convergence.

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An Empirical Comparison of Discrete Estimation of Distribution Algorithmsempirical comparison is carried out in relation with three different criteria: the convergence velocity, the convergence reliability and the scalability. Different function sets are optimized depending on the aspect to evaluate.

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Book 2002thispart, after introducing some probabilistic graphical models -Bayesian and Gaussian networks - a review of existing EDAapproaches is presented, as well as some new methods based on moreflexible probabilistic graphical models. A mathematical modeling ofdiscrete EDAs is also presented. Part II cove

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1568-2587 ented, as well as some new methods based on moreflexible probabilistic graphical models. A mathematical modeling ofdiscrete EDAs is also presented. Part II cove978-1-4613-5604-2978-1-4615-1539-5Series ISSN 1568-2587

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