Integration of Biologically Inspired Temporal Mechanisms into a Cortical Framework for Sequence Processing

Hervé Frezza-Buet 1 Nicolas P. Rougier 1 Frédéric Alexandre 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Whereas classical connectionist models can hardly cope with difficult dynamic tasks with a strong temporal factor, many temporal mechanisms inspired with neurobiological data has been proposed in the past and yield efficient time processing properties. The goal of this chapter is to show that, beyond these isolated mechanisms, their integration in a more general architectural and functional framework can potentiate their power and make them usable for non trivial behavioral tasks. We propose a cerebral framework, from the neuronal to the behavioral level, and give some applicative illustrations that underline the encouraging results obtained today.
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Chapitre d'ouvrage
none. Neural, Symbolic and Reinforcement Methods for Sequence Learning, Springer, 28 p, 2000
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Soumis le : jeudi 19 octobre 2006 - 09:12:00
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48
Document(s) archivé(s) le : vendredi 25 novembre 2016 - 12:40:01

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Hervé Frezza-Buet, Nicolas P. Rougier, Frédéric Alexandre. Integration of Biologically Inspired Temporal Mechanisms into a Cortical Framework for Sequence Processing. none. Neural, Symbolic and Reinforcement Methods for Sequence Learning, Springer, 28 p, 2000. 〈inria-00107857〉

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