Fostering common ground in human-robot interaction

Abstract

Effective communication between people and interactive robots would benefit if they have a common ground of understanding. I discuss how the common ground principle of least collective effort can be used to predict and design human robot interactions. Social cues lead people to create a mental model of a robot and estimates of its knowledge. People's mental model and knowledge estimate would, in turn, influence the effort they expend to communicate with the robot. People would explain their message in less detail to a knowledgeable robot with which they have more common ground. This process can be leveraged to design interactions that have an appropriate style of robot direction and that accommodate to differences among people.