Improving Humanness of Virtual Agents and Users' Cooperation through Emotions

In this paper, we analyze the performance of an agent developed according to a well-accepted appraisal theory of human emotion with respect to how it modulates play in the context of a social dilemma. We ask if the agent will be capable of generating interactions that are considered to be more human than machine-like. We conducted an experiment with 117 participants and show how participants rated our agent on dimensions of human-uniqueness (separating humans from animals) and human-nature (separating humans from machines). We show that our appraisal theoretic agent is perceived to be more human-like than the baseline models, by significantly improving both human-nature and human-uniqueness aspects of the intelligent agent. We also show that perception of humanness positively affects enjoyment and cooperation in the social dilemma, and discuss consequences for the task duration recall.