Entropic divergence for population based optimization algorithms

Vincenzo Cutello*, Giuseppe Nicosia, Mario Pavone, Giovanni Stracquadanio

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The concept of information gain has been adopted as tool to study the effectiveness of population-based optimizers; using this approach, it is possible to infer convergence properties for population-based optimizers. The experimental results have shown characteristic phase transition between exploration and exploitation phase during the evolutionary process and, moreover, the evidence that gain maximization offers a robust theoretical framework to study the convergence of stochastic optimizers.

Original languageEnglish
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs
Publication statusPublished - 1 Dec 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain
Duration: 18 Jul 201023 Jul 2010

Conference

Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Country/TerritorySpain
CityBarcelona
Period18/07/1023/07/10

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