This article surveys the area of computational empathy, analysing different ways by which artificial agents can simulate and trigger empathy in their interactions with humans. Empathic agents can be seen as agents that have the capacity to place themselves into the position of a user’s or another agent’s emotional situation and respond appropriately. We also survey artificial agents that, by their design and behaviour, can lead users to respond emotionally as if they were experiencing the agent’s situation. In the course of this survey, we present the research conducted to date on empathic agents in light of the principles and mechanisms of empathy found in humans. We end by discussing some of the main challenges that this exciting area will be facing in the future.

Empathy can be defined as the ability to perceive and understand others' emotional states. Neuropsychological evidence has shown that humans empathize with each other to different degrees depending on factors such as their mood, personality, and social relationships. Although artificial agents have been endowed with features such as affect, personality, and the ability to build social relationships, little attention has been devoted to the role of such features as factors that can modulate their empathic behavior. In this paper, we present and discuss the results of an empirical evaluation of a computational model of empathy which allows a virtual human to exhibit different degrees of empathy. Our model is supported by psychological models of empathy and is applied and evaluated in the context of a conversational agent scenario.

Expressing and recognizing affective states with respect to facial expressions is an important aspect in perceiving virtual humans as more natural and believable. Based on the results of an empirical study a system for simulating emotional facial expressions for a virtual human has been evolved. This system consists of two parts: (1) a control architecture for simulating emotional facial expressions with respect to Pleasure, Arousal, and Dominance (PAD) values, (2) an expressive output component for animating the virtual human's facial muscle actions called Action Units (AUs), modeled following the Facial Action Coding System (FACS). A large face repertoire of about 6000 faces arranged in PAD-space with respect to two dominance values (dominant vs. submissive) is obtained as a result of the empirical study. Using the face repertoire an approach towards realizing facial mimicry for a virtual human based on backward mapping AUs displaying an emotional facial expression on PAD-values is outlined. A preliminary evaluation of this first approach is realized with AUs corresponding to the basic emotions Happy and Angry.

Allowing virtual humans to align to others' perceived emotions is believed to enhance their cooperative and communicative social skills. In our work, emotional alignment is realized by endowing a virtual human with the ability to empathize. Recent research shows that humans empathize with each other to different degrees depending on several factors including, among others, their mood, their personality, and their social relationships. Although providing virtual humans with features like affect, personality, and the ability to build social relationships, little attention has been devoted to the role of such features as factors modulating their empathic behavior. Supported by psychological models of empathy, we propose an approach to model empathy for the virtual human EMMA-an Empathic MultiModal Agent-consisting of three processing steps: First, the Empathy Mechanism by which an empathic emotion is produced. Second, the Empathy Modulation by which the empathic emotion is modulated. Third, the Expression of Empathy by which EMMA's multiple modalities are triggered through the modulated empathic emotion. The proposed model of empathy is illustrated in a conversational agent scenario involving the virtual humans MAX and EMMA.

Abstract. Endowing artificial agents with the ability to empathize is believed to enhance their social behavior and to make them more likable, trustworthy, and caring. Neuropsychological findings substantiate that empathy occurs to different degrees depending on several factors including, among others, a person's mood, personality, and social relationships with others. Although there is increasing interest in endowing artificial agents with affect, personality, and the ability to build social relationships, little attention has been devoted to the role of such factors in influencing their empathic behavior. In this paper, we present a computational model of empathy which allows a virtual human to exhibit different degrees of empathy. The presented model is based on psychological models of empathy and is applied and evaluated in the context of a conversational agent scenario.