MN-EDA and the Use of Clique-Based Factorisations in EDAs

MN-EDA and the Use of Clique-Based Factorisations in EDAs” by R. Santana. In Markov Networks in Evolutionary Computation, (S. Shakya and R. Santana, eds.), 2012, pp. 73-87.

Abstract

This chapter discusses the important role played by factorisations in the study of EDAs and presents the Markov network estimation of distribution algorithm (MN-EDA) as a classical example of the EDAs based on the use of undirected graphs. The chapter also reviews recent work on the use of clique-based decompositions and other approximations methods inspired in the field of statistical physics with direct application to EDAs.

BibTeX entry:

@incollection{Santana:2012,
   author = {R. Santana},
   editor = {S. Shakya and R. Santana},
   title = {MN-EDA and the Use of Clique-Based Factorisations in EDAs},
   booktitle = {Markov Networks in Evolutionary Computation},
   pages = {73-87},
   publisher = {Springer},
   year = {2012},
   url = {http://dx.doi.org/10.1007/978-3-642-28900-2_5}
}

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