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An Agent Model Using Polychronous Networks

Julio Monteiro Philippe Caillou 1, 2 Marco Netto 3 
1 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
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 Connect in order to contact the contributor
Submitted on : Tuesday, June 9, 2009 - 2:18:10 PM
Last modification on : Sunday, June 26, 2022 - 11:49:57 AM

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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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