A Framework for Situation-Based Social Interaction
Abstract
This paper presents a theoretical framework for
computationally representing social situations in a robot. This
work is based on interdependence theory, a social psychological
theory of interaction and social situation analysis. We use
interdependence theory to garner information about the social
situations involving a human and a robot. We also quantify the
gain in outcome resulting from situation analysis. Experiments
demonstrate the utility of social situation information and of our
situation-based framework as a method for guiding robot
interaction. We conclude that this framework offers a principled,
general approach for studying interactive robotics problems.