The challenges of developmental robotics
Pierre-Yves Oudeyer (INRIA, Bordeaux)
Developmental robotics aim at building robots which, once "out of the factory" and in the "wild" of the real-world, should be capable of learning cumulatively an open-ended repertoire of new skills, both through self-experimentation and social interaction with humans. A major challenge that has to be faced is that the sensorimotor spaces encountered by such robots, including the interaction of their body with novel external objects and persons, are high-volume, high-dimensional, unbounded and partially unlearnable. If one wants robots to be capable of efficient learning in such spaces, one must take inspiration from infant development which shows the importance of various families of developmental constraints. In this talk, I will review several of these constraints, including mechanisms for curiosity-driven learning, maturation, sensorimotor primitives, joint attention and joint intention in social guidance, self-organization, and morphological computation, and show how they can allow to transform apparently daunting machine learning problems into much more tractable problems.