Structuring Human-Robot-Interaction in Tutoring Scenarios
Contrary to the assumptions underlying many current robot systems, teaching is an interactive process where the tutor needs to be continuously informed about the learner’s internal states of understanding and perception. In an open ended learning situation this interaction can not be pre-modelled as the aspects that need clarification can not be foreseen. However, standard approaches do exactly this: they pre-define interactions by coupling system states with dialog acts. In our approach we target at losening this coupling between system and dialog states by providing general task and interaction patterns and means to relate them to each other.
By this approach we are now able to provide on the one hand a dialog system that is relatively easily adaptable to new scenarios and on the other hand mixed-initiative interactions that allow the system to inform the tutor about internal representations when they become important for the interaction.
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