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Genetic algorithms and grid computing for artificial embryogeny

Sylvain Cussat-Blanc 1 Fabien Viale 2 Hervé Luga 1 Yves Duthen 3 Denis Caromel 2
1 IRIT-VORTEX - Visual Objects from Reality To Expression
IRIT - Institut de recherche en informatique de Toulouse
2 OASIS - Active objects, semantics, Internet and security
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - COMRED - COMmunications, Réseaux, systèmes Embarqués et Distribués
3 IRIT-TCI - Traitement et Compréhension d’Images
IRIT - Institut de recherche en informatique de Toulouse
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.
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Contributor : Ist Rennes <>
Submitted on : Thursday, April 12, 2012 - 2:46:59 PM
Last modification on : Thursday, March 18, 2021 - 2:16:21 PM



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, ⟨10.1145/1389095.1389139⟩. ⟨hal-00687153⟩



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