A basal ganglia inspired model of action selection evaluated in a robotic survival task

Benoît Girard (1) , Vincent Cuzin (1) , Agnès Guillot (1) , Kevin Gurney (2) , Tony Prescott (2)

1 OASIS - Objets et Agents pour Systèmes d'Information et Simulation
2 ABRG - Adaptive Behaviour Research Group

The basal ganglia system has been proposed as a possible neural substrate for action selection in the vertebrate brain. We describe a robotic implementation of a model of the basal ganglia and demonstrate the capacity of this system to generate adaptive switching between several acts when embedded in a robot that has to ‘survive' in a laboratory environment. A comparison between this brain-inspired selection mechanism and classical `winner-takes-all\' selection highlights some adaptive properties specific to the model, such as avoidance of dithering and energy-saving. These properties derive, in part, from the capacity of simulated basal ganglia-thalamo-cortical loops to generate appropriate ‘behavioural persistence'.

Mots clés: biorobotics; basal ganglia; action selection; computational model; survival task

Domaines: Neurosciences; Intelligence artificielle [cs.AI]; Recherche opérationnelle [math.OC]

Benoît Girard, Vincent Cuzin, Agnès Guillot, Kevin Gurney, Tony Prescott. A basal ganglia inspired model of action selection evaluated in a robotic survival task. Journal of Integrative Neuroscience, 2003, 2 (3), pp.179-200. ⟨10.1142/S0219635203000299⟩. ⟨hal-00016392⟩