Using Copulas in Estimation of Distribution Algorithms

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 distribut...

Full description

Saved in:
Bibliographic Details
Published inMICAI 2009: Advances in Artificial Intelligence pp. 658 - 668
Main Authors Salinas-Gutiérrez, Rogelio, Hernández-Aguirre, Arturo, Villa-Diharce, Enrique R.
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Bayesian Network
Copula Function
Copula Modeling
Marginal Distribution
Mutual Information
Online AccessGet full text

Cover

More Information
Summary: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.
ISBN:3642052576
9783642052576
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-05258-3_58