Abstract
A new way of modeling probabilistic dependencies in Estimation of Distribution Algorithm (EDAs) is presented. By means of copulas it is possible to separate the structure of dependence from marginal distributions in a joint distribution. The use of copulas as a mechanism for modeling joint distributions and its application to EDAs is illustrated on several benchmark examples.
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Salinas-Gutiérrez, R., Hernández-Aguirre, A., Villa-Diharce, E.R. (2009). Using Copulas in Estimation of Distribution Algorithms. In: Aguirre, A.H., Borja, R.M., Garciá, C.A.R. (eds) MICAI 2009: Advances in Artificial Intelligence. MICAI 2009. Lecture Notes in Computer Science(), vol 5845. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05258-3_58
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DOI: https://doi.org/10.1007/978-3-642-05258-3_58
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