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Learning and control with chaos: From biology to robotics

Published online by Cambridge University Press:  15 November 2002

Mathias Quoy,
Jean-Paul Banquet and
Emmanuel Daucé
Mathias Quoy
Affiliation:
Neurocybernetics Group, ETIS Lab, Université de Cergy-Pontoise, Cergy-Pontoise, 95014, France quoy@u-cergy.fr www-etis.ensea.fr/~quoy/perso.html
Jean-Paul Banquet
Affiliation:
Neuroscience et modélisation, Université Pierre et Marie Curie, Paris, 75252, France banquet@ccr.jussieu.fr
Emmanuel Daucé
Affiliation:
CERT-ONERA-DTIM, Toulouse, 31400, France dauce@cert.fr www.cert.fr/anglais/deri/dauce
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Abstract

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After critical appraisal of mathematical and biological characteristics of the model, we discuss how a classical hippocampal neural network expresses functions similar to those of the chaotic model, and then present an alternative stimulus-driven chaotic random recurrent neural network (RRNN) that learns patterns as well as sequences, and controls the navigation of a mobile robot.

Information

Type
Brief Report
Information
Behavioral and Brain Sciences , Volume 24 , Issue 5 , October 2001, pp. 824 - 825
Copyright
© 2001 Cambridge University Press