Neuromodelling based on evolutionary robotics: on the importance of motor control for spatial attention

Mainstream approaches to modelling cognitive processes have typically focused on (1) reproducing their neural underpinning, without regard to sensory-motor systems and (2) producing a single, ideal computational model. Evolutionary robotics is an alternative possibility to bridge the gap between neural substrate and behavior by means of a sensory-motor apparatus, and a powerful tool to build a population of individuals rather than a single model. We trained 4 populations of neurorobots, equipped with a pan/tilt/zoom camera, and provided with different types of motor control in order to perform a cancellation task, often used to tap spatial cognition. Neurorobots' eye movements were controlled by (a) position, (b) velocity, (c) simulated muscles and (d) simulated muscles with fixed level of zoom. Neurorobots provided with muscle and velocity control showed better performances than those controlled in position. This is an interesting result since muscle control can be considered a particular type of position control. Finally, neurorobots provided with muscle control and zoom outperformed those without zooming ability.