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conference paper
Goal-Directed Imitation in a Humanoid Robot
2005
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Our work aims at developing a robust discriminant controller for robot programming by demonstration. It addresses two core issues of imitation learning, namely "what to imitate" and "how to imitate". This paper presents a method by which a robot extracts the goals of a demonstrated task and determines the imitation strategy that satisfies best these goals. The method is validated in a humanoid platform, taking inspiration of an influential experiment from developmental psychology.
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