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

Benoît Girard (1) , N Tabareau , Q C Pham (2) , A. Berthoz (3) , J.-J C Slotine (4)

1 ISIR - Institut des Systèmes Intelligents et de Robotique
2 LCA - Laboratory for Computer Communications and Applications
3 LPPA - Laboratoire de Physiologie de la Perception et de l'Action
4 MIT - Massachusetts Institute of Technology

Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multidisciplinary approach at the convergence of neuro-science, dynamical systems 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 neu-ral 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.

Mots clés: basal ganglia; action selection; contraction analysis; autonomous robotics; computational model

Domaines: Neurosciences; Robotique [cs.RO]; Réseau de neurones [cs.NE]; Intelligence artificielle [cs.AI]

Benoît Girard, N Tabareau, Q C Pham, A. Berthoz, J.-J C Slotine. Where neuroscience and dynamic system theory meet autonomous robotics: A contracting basal ganglia model for action selection. Neural Networks, 2008, 21 (4), pp.628- 641. ⟨10.1016/j.neunet.2008.03.009⟩. ⟨hal-01524676⟩