Empathy-Aware Behavior Trees for Social Care Decision Systems

Abstract

There is growing attention on the importance of building intelligent systems where humans and Artificial Intelligence-based systems (AIs) form teams exploiting the potentially synergistic relationships between humans and automation. In the last decade, the computational modeling of empathy has gained increasing attention. Empowering interactive agents with empathic capabilities leads, on the human’s side, to more trust, increases engagement, and thus interaction length, helps cope with stress. These findings suggest that agents endowed with empathy may enhance social interaction in educational applications, artificial companions, medical assistants, and gaming applications. This article focuses on modeling the empathic behavior of virtual agents interacting with humans. We propose a formal model that enables virtual agents to exhibit empathic, emotional behavior. Specifically, we extend the modeling of empathy via behavior trees with a new type of node allowing the specification of various kinds of empathy. Using the proposed extension, we show how different agents’ reactive behavior can be modeled.