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Neuronal mechanisms for sequence learning in behavioral modeling

Nicolas P. Rougier 1 Hervé Frezza-Buet 1 Frédéric Alexandre 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Sequence learning and management have been reported as central features in behavioral studies. Indeed, tasks like route memorization or planning are temporal behaviors and can be hardly modeled without taking the temporal aspect into consideration. On the contrary, classical information processing tools are not very efficient at such temporal processing. In this paper, we shortly review these tools and show that another approach, close to neurobiological modeling, can yield a variety of neuronal mechanisms for several aspects of sequence learning and management.
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https://hal.inria.fr/inria-00098756
Contributor : Publications Loria <>
Submitted on : Tuesday, September 26, 2006 - 8:33:21 AM
Last modification on : Friday, February 26, 2021 - 3:28:03 PM
Long-term archiving on: : Wednesday, March 29, 2017 - 12:34:07 PM

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  • HAL Id : inria-00098756, version 1

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Nicolas P. Rougier, Hervé Frezza-Buet, Frédéric Alexandre. Neuronal mechanisms for sequence learning in behavioral modeling. Sixteenth International Joint Conference on Artificial Intelligence, Workshop : Neural, Symbolic, and Reinforcement Methods for Sequence Learning, 1999, Stockholm, Sweden, 6 p. ⟨inria-00098756⟩

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