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.