Three Avatars Walk into a Bar: Defining and Evaluating Realism for Virtual Supporting Characters

Convincing and compelling virtual environments that are populated with rich characters demand consistent, nuanced, and realistic behavior that is integrated in the surrounding environment. We introduce the concept of Supporting Character Realism (SCR) for virtual avatars by identifying the capabilities of agents which have the ability to work in tandem with traditional “main character realism” approaches by demonstrating consistent and nuanced behaviors that blend into the surrounding background environment. Next, we propose several metrics for evaluating agents attempting to achieve this level of realism and test our proposed metrics in a social interaction experiment set in a virtual bar amidst a variety of human and computer controlled patrons. Finally, we employ these metrics to measure the SCR performance of traditional scripted bots and prototype AI-driven agents. Our results show that SCR is not only a distinguishable and measurable metric of agent realism, but also a technically achievable goal within the reach of modern AI techniques.