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A Multi-Cellular Developmental System in Continuous Space using Cell Migration

Nicolas Bredeche 1, 2
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 introduces a novel multi-cellular developmental system where cells are placed in a continuous space. Cells communicate by diffusing and perceiving substances in the environment and are able to migrate around following affinities with substance gradients. The optimization process is performed using Echo State neural networks on the problem of minimizing tile size variations in the context of a tiling problem. Experimental results show that problem complexity only impacts the number of substances used, rather than the number of cells, which implies some sort of scalability with regards to the size of the phenotype. Symmetry breaking and robustness are addressed by adding noise as an intrinsic property of the model. A (positive) side effect is that the resulting model produces very robust solutions with efficient self-healing behavior in the presence of perturbations never met before.
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Contributor : Nicolas Bredeche <>
Submitted on : Friday, June 13, 2008 - 4:22:09 PM
Last modification on : Thursday, July 8, 2021 - 3:48:41 AM
Long-term archiving on: : Friday, September 28, 2012 - 4:00:44 PM


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  • HAL Id : inria-00288037, version 1



Nicolas Bredeche. A Multi-Cellular Developmental System in Continuous Space using Cell Migration. Simulation of Adaptive Behavior, Jul 2008, Osaka, Japan. ⟨inria-00288037⟩



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