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

Abstract : 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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https://hal.archives-ouvertes.fr/hal-01524676
Contributor : Benoît Girard <>
Submitted on : Thursday, May 18, 2017 - 4:01:00 PM
Last modification on : Tuesday, December 8, 2020 - 3:39:12 AM

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

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