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