Team Performance and User Satisfaction in Mixed Human-Agent Teams.

Human-agent teams, consisting of at least one human and one agent teaming together to achieve a common objective, are increasingly prevalent and effective in both social and industrial spheres. Associated changes in human preferences and expectations from autonomous teammates will continue to shape and alter collaboration opportunities and dynamics within human-agent teams. New environments are emerging, including Ad Hoc teams where teammates collaborate without pre-coordination or prior knowledge of other teammates capabilities. Team members in ad hoc human-agent teams have to collaborate to find tasks allocations to effectively leverage teammate capabilities to improve team performance and human satisfaction. In this paper, we investigate ad hoc team dynamics under different team compositions, including those comprised of only humans or of human and agent team members, as well as teams consisting of more than two members. Experiments are run with MTurk workers and several hypotheses are evaluated on the effects of teammate type and team size on team performance and human satisfaction using a collaborative Human-Agent Taskboard (CHATboard) platform where teams repeatedly collaborate to complete assigned tasks.