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Artificial Gene Regulatory Networks and Spatial Computation: A Case Study

Sylvain Cussat-Blanc 1 Nicolas Bredeche 2, 3 Hervé Luga 1 Yves Duthen 1 Marc Schoenauer 2, 4
2 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : This paper explores temporal and spatial dynamics of a population of Genetic Regulatory Networks (GRN). In order to so, a GRN model is spatially distributed to solve a multi-cellular Artificial Embryogeny problem, and Evolutionary Computation is used to optimize the developmental sequences. An in-depth analysis is provided and show that such a population of GRN display strong spatial synchronization as well as various kind of behavioral patterns, ranging from smooth diffusion to abrupt transition patterns.
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Contributor : Sylvain Cussat-Blanc <>
Submitted on : Monday, June 20, 2011 - 4:17:02 PM
Last modification on : Wednesday, April 8, 2020 - 4:02:58 PM


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  • HAL Id : inria-00601816, version 1


Sylvain Cussat-Blanc, Nicolas Bredeche, Hervé Luga, Yves Duthen, Marc Schoenauer. Artificial Gene Regulatory Networks and Spatial Computation: A Case Study. ECAL, Aug 2011, Paris, France. ⟨inria-00601816⟩



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