2008 Special Issue: Where neuroscience and dynamic system theory meet autonomous robotics: A contracting basal ganglia model for action selection

  • Authors:

  • B. Girard;N. Tabareau;Q. C. Pham;A. Berthoz;J. -J. Slotine

  • Affiliations:

  • Laboratoire de Physiologie de la Perception et de l'Action, UMR7152, CNRS - Collège de France, 11 place Marcelin Berthelot, 75231 Paris Cedex 05, France;Laboratoire de Physiologie de la Perception et de l'Action, UMR7152, CNRS - Collège de France, 11 place Marcelin Berthelot, 75231 Paris Cedex 05, France;Laboratoire de Physiologie de la Perception et de l'Action, UMR7152, CNRS - Collège de France, 11 place Marcelin Berthelot, 75231 Paris Cedex 05, France;Laboratoire de Physiologie de la Perception et de l'Action, UMR7152, CNRS - Collège de France, 11 place Marcelin Berthelot, 75231 Paris Cedex 05, France;Nonlinear Systems Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

  • Venue:
  • Neural Networks
  • Year:
  • 2008

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Abstract

Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multi-disciplinary approach at the convergence of neuroscience, dynamical system theory and autonomous robotics, in order to propose an efficient action selection mechanism based on a new model of the basal ganglia. We first describe new developments of contraction theory regarding locally projected dynamical systems. We exploit these results to design a stable computational model of the cortico-baso-thalamo-cortical loops. Based on recent anatomical data, we include usually neglected neural projections, which participate in performing accurate selection. Finally, the efficiency of this model as an autonomous robot action selection mechanism is assessed in a standard survival task. The model exhibits valuable dithering avoidance and energy-saving properties, when compared with a simple if-then-else decision rule.