Abstract : Genetic algorithms are very demanding in terms of computing time and, when the population size is large, they need days to complete or even fail due to memory restrictions. It is particularly the case for artificial life where each evaluation can take more than one minute to develop an artificial creature, plant or organism. Indeed, creatures are developed in physical and chemical simulators that require important computation resources. In order to create more and more realistic creatures, we propose a grid parallelized version of genetic algorithms. Two possibilities exist to increase them: supercomputers or computational grids. Because of their scalability, we choose computational grid in their works.
Type de document :
Communication dans un congrès
GECCO '08 Proceedings of the 10th annual conference on Genetic and evolutionary computation, Jul 2008, Atlanta, United States. pp.281-282, 2008, <10.1145/1389095.1389139>
https://hal.inria.fr/hal-00687153
Contributeur : Ist Rennes <>
Soumis le : jeudi 12 avril 2012 - 14:46:59
Dernière modification le : mardi 21 juin 2016 - 01:05:15
Sylvain Cussat-Blanc, Fabien Viale, Hervé Luga, Yves Duthen, Denis Caromel. Genetic algorithms and grid computing for artificial embryogeny. GECCO '08 Proceedings of the 10th annual conference on Genetic and evolutionary computation, Jul 2008, Atlanta, United States. pp.281-282, 2008, <10.1145/1389095.1389139>. <hal-00687153>
