Gianluca Baldassarre, ISTC-CNR, Italy
Bio-inspired computational models of the development of attention skills: intrinsic motivations, goals, and learning
Abstract: I will first introduce a novel European Project supporting this research (``GOAL-Robots’’), and then present some computational models aiming to identify the cognitive architecture and mechanisms that might underlay the autonomous development of overt attention skills in children and robots. The models propose possible key functions, and underlying mechanisms, needed for the autonomous acquistion of attention skills: a fixed stimulus-based bottom-up attention component, a reinforcement learning top-down attention component, the coupling of eye/arm control, the self-generation of goals, intrinsic motivationsguiding autonomous learning and their coordination with extrinsic motivations. The modelswere developed using three sources of constraints; (a) behavioural functions/learning processes that, within embodied systems, seem broadly needed to produce the observable development of children; (b) data from developmental psychology experiments; © knowledge on the broad organisation of the brain system underlying attention control. Overall, the models represent tools for interpreting existing empirical experiments andsuggesting new ones.
Back to the symposium’s table of contents