Grounding Communication Without Prior Structure

This work describes an approach to time-series modeling of social interactions between human and robot, which is motivated by the social psychology concept of social grounding. In this model, the goal of the agents is to establish and use patterns of communication, rather than rely on existing patterns. Our goal is to allow an artifical agent to construct a pattern of shared meaning with a human or other agent through shared experience rather than relying a model provided A priori. We describe a preliminary human robot interaction study which illustrates the proposed approach.