Improving Humanness of Virtual Agents and Users' Cooperation through Emotions
This work addresses the challenge of enhancing human-agent interaction in social settings, though it is incremental as it builds on existing appraisal theories.
The paper tackled the problem of making virtual agents appear more human-like in social dilemmas, and found that an appraisal theory-based agent significantly improved perceived humanness and positively affected user enjoyment and cooperation.
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 conduct an experiment with 117 participants and show how participants rate our agent on dimensions of human-uniqueness (which separates humans from animals) and human-nature (which separates humans from machines). We show that our appraisal theoretic agent is perceived to be more human-like than 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.