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. © 2009 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Salinas-Gutiérrez, R., Hernández-Aguirre, A., & Villa-Diharce, E. R. (2009). Using copulas in estimation of distribution algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5845 LNAI, pp. 658–668). https://doi.org/10.1007/978-3-642-05258-3_58
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
