Home /Research /Learning and control with chaos: From biology to robotics
LEARNING

Learning and control with chaos: From biology to robotics

Mathias Quoy, Jean-Paul Banquet, Emmanuel Daucé

Year
2001
Citations
4

Abstract

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.

Keywords

ChaoticArtificial intelligenceArtificial neural networkCHAOS (operating system)Computer scienceRoboticsHippocampal formationCognitive scienceNeuroscienceRobot

Related papers

Browse all LEARNING papers