The current research presents an original model allowing a machine to acquire new behaviors via its cooperative interaction with a human user. One of specificities of this system is to place the interaction at the heart of the learning. Thus, as one proceeds with exchanges, the robot improves its behaviors favoring a smoother and more natural interaction. Two experiments demonstrate the robustness of this approach in learning composite perceptual-motor behavioral sequences of varying complexity.
['Jean-David Boucher', 'Peter Ford Dominey']
Programming by Cooperation: Perceptual-Motor Sequence Learning via Human-Robot Interaction