Self-explaining Agents: A Study in the BW4T Testbed for Team Coordination

摘要

There are several applications in which humans and agents jointly perform a task. If the task involves interdependence among the team members, coordination is required to achieve good team performance. Coordination in human-agent teams can be improved by giving humans insight in the behavior of the agents. When humans are able to understand and predict an agent's behavior, they can more easily adapt their own behavior to that of the agent. One way to achieve such understanding is by letting agents explain their behavior. This report presents a study in the BW4T coordination testbed that examines the effects of agents explaining their behavior on coordination in human-agent teams. The results show that explanations about agent behavior do not always lead to better team performance, but they do impact the user experience in a positive way.