Sinopsis
From the content: Probabilistic Graphical Models and Markov Networks.- A review of Estimation of Distribution Algorithms and Markov networks.- MOA - Markovian Optimisation Algorithm.- DEUM - Distribution Estimation Using Markov Networks.- MN-EDA and the use of clique-based factorisations in EDAs.- Convergence Theorems of Estimation of Distribution Algorithms.- Adaptive Evolutionary Algorithm based on a Cliqued Gibbs Sampling over Graphical Markov Model Structure.
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