PUB - Publikationen an der Universität Bielefeld

In learning tasks, interaction is mostly about the exchange of knowledge. The interaction process shall be governed on the one hand by the knowledge the tutor wants to convey and on the other by the lacks of knowledge of the learner. In human-robot interaction (HRI), it is usually the human demonstrating or explicitly verbalizing her knowledge and the robot acquiring a respective representation. The ultimate goal in interactive robot learning is thus to enable inexperienced, untrained users to tutor robots in a most natural and intuitive manner. This goal is often impeded by a lack of knowledge of the human about the internal processing and expectations of the robot and by the inflexibility of the robot to understand open-ended, unconstrained tutoring or demonstration. Hence, we propose mixed-initiative strategies to allow both to mutually contribute to the interactive learning process as a bi-directional negotiation about knowledge. Along this line this paper discusses two initially different case studies on object manipulation and learning of spatial environments. We present different styles of mixed-initiative in these scenarios and discuss the merits in each case.