Neural clustering analysis of macroevolutionary and genetic algorithms in the evolution of robot controllers

Authors:
J. A. Becerra;J. Santos
Affiliations:
Grupo de Sistemas Autónomos, Departamento de Computación, Facultade de Informática, Universidade da Coruña;Grupo de Sistemas Autónomos, Departamento de Computación, Facultade de Informática, Universidade da Coruña
Venue:
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Year:
2005

Citing 4
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Abstract

In this work, we will use self-organizing feature maps as a method of visualization the sampling of the fitness space considered by the populations of two evolutionary methods, genetic and macroevolutionary algorithms, in a case with a mostly flat fitness landscape and low populations. Macroevolutionary algorithms will allow obtaining better results due to the way in which they handle the exploration-exploitation equilibrium. We test it with different alternatives using the self-organizing maps.