An Agent Model Using Polychronous Networks

Julio Monteiro Philippe Caillou 1, 2 Marco Netto 3
1 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 : In this paper, we present an agent model based on computation with polychronous groups on spiked neural networks, that is able to learn to return to known initial situations, without any guidance
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https://hal.inria.fr/inria-00393065
Contributor : Philippe Caillou <>
Submitted on : Tuesday, June 9, 2009 - 2:18:10 PM
Last modification on : Tuesday, February 12, 2019 - 4:25:00 PM

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  • HAL Id : inria-00393065, version 1

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Julio Monteiro, Philippe Caillou, Marco Netto. An Agent Model Using Polychronous Networks. Colibri, Jul 2009, Bento Gonçalves, Brazil. pp.76-80. ⟨inria-00393065⟩

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