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Evolving genetic regulatory networks for online neurogenesis

Dennis Wilson 1 Sylvain Cussat-Blanc 1 Hervé Luga 1
1 IRIT-REVA - Real Expression Artificial Life
IRIT - Institut de recherche en informatique de Toulouse
Abstract : We evolve a Genetic Regulatory Network (GRN) in a three dimensional morphogen gradient environment to determine the topology of the neurons in a Spiking Neural Network (SNN). A genetic algorithm is used to optimize the GRN, selecting individuals based on the performance of the SNN grown by the GRN. Performance is measured on two tasks: visual discrimination and robotic foraging. Early results show potential for this method as both an indirect encoding and on-line regulator of neural networks.
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Submitted on : Wednesday, May 2, 2018 - 9:46:56 AM
Last modification on : Tuesday, September 8, 2020 - 10:38:02 AM
Long-term archiving on: : Tuesday, September 25, 2018 - 9:06:40 AM


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  • HAL Id : hal-01782556, version 1
  • OATAO : 18939


Dennis Wilson, Sylvain Cussat-Blanc, Hervé Luga. Evolving genetic regulatory networks for online neurogenesis. 6th Morphogenetic Engineering Workshop (MEW 2016) at ALife XV : Artificial Life Conference, Jul 2016, Cancun, Mexico. pp. 14-15. ⟨hal-01782556⟩



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