Evolving genetic regulatory networks for online neurogenesis
Résumé
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.
Origine | Fichiers produits par l'(les) auteur(s) |
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