Computational delays and habits

The Brain is a slow computer yet humans can skilfully play games where very fast reactions are required. A solution to that problem is to bypass the slow action planning process and map directly perceptions to plans. It is proposed that the cerebellum has a dual function: Whereas in the intermediate and medial areas, it has the well known function of an inverse model of the motor system, in its lateral zone, it learns which plans are the most approriate responses to a set of future perceptual situations, for a given goal, and preselects via cerebrocortical projections them for execution under sensory triggering. This scheme saves planning time but, in absence of cognitive gating, enables sometimes inappropriate habitual behaviour. Hence habits may be a by-product of a computational strategy designed for compensating for computational planning delays. Robot control strategies inspired by the cerebellum are proposed, whereby planning is performed off-line and fed to a sequence learning system or task specific sets of plans are prepared in advance for fast selection using sensory inputs. Such schemes have been implemented using artificial neural networks.