HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Neuronal mechanisms for sequence learning in behavioral modeling

Nicolas 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.
Document type :
Conference papers
Complete list of metadata

Contributor : Publications Loria Connect in order to contact the contributor
Submitted on : Tuesday, September 26, 2006 - 8:33:21 AM
Last modification on : Friday, February 4, 2022 - 3:14:37 AM
Long-term archiving on: : Wednesday, March 29, 2017 - 12:34:07 PM


  • HAL Id : inria-00098756, version 1



Nicolas 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⟩



Record views


Files downloads