Learning by Feeling: Evoking Empathy With Synthetic Characters

Paiva, Ana; Dias, João; Sobral, Daniel; Aylett, Ruth; Woods, Sarah; Hall, Lynne; Zoll, Carsten

doi:10.1080/08839510590910165

Cited by 133 publications

(70 citation statements)

References 15 publications

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“…Among all visual forms, the blob was most preferred and this favourable impression generalized across other characteristics (i.e., mind, trustworthiness). In accordance with previous research, for children a human-like appearance may therefore not be a direct criterion for inferring the agents' abilities [e.g., 5,6].…”

Section: Discussionmentioning

confidence: 52%

“…To elucidate this question, we selected attributes that target dispositional traits, mental states, as well as basic and complex emotions. Whereas simple traits and emotions (e.g., likeable, trustworthy, angry) may be easily attributed to mechanical and animal looking characters, abstract concepts such as mind and shame require more cognitive complexity than what might be apparent on first sight [5,6,7]. Based on previous research [8,9] we predicted that the degree of human-likeness would significantly affect adults' attributions as to the agent's mental and emotional capabilities.…”

Section: Introductionmentioning

confidence: 99%

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From Non-human to Human: Adult’s and Children’s Perceptions of Agents Varying in Humanness

Krumhuber

Kappas

Hume

et al. 2015

Intelligent Virtual Agents

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Abstract. While most interface agents have been designed from an adult perspective, the present paper compares adults' and children's views of agents that vary in their degree of humanness. Four synthetic characters ranging in appearance from non-human to very human (blob, cat, cartoon, human) were presented to adult and children perceivers and were evaluated with respect to their cognitive and emotional abilities. The visual appearance significantly influenced participants' ratings in both age groups. However, the pattern of results was more differentiated for adult perceivers as a function of the humanlikeness of the character. The findings suggest that children may rely less on human-like features in inferring agents' capabilities which are judged along simpler cognitive and social dimensions. Implications for the design of artificial agents are discussed.

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Section: Discussionmentioning

confidence: 52%

Section: Introductionmentioning

confidence: 99%

From Non-human to Human: Adult’s and Children’s Perceptions of Agents Varying in Humanness

Krumhuber

Kappas

Hume

et al. 2015

Intelligent Virtual Agents

Self Cite

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“…An example of work that adopted the 'character-based' approach is the software FearNot! [10]. In FearNot!, characters run the FAtiMA [11] architecture, including a generative planner.…”

Section: State-of-the-artmentioning

confidence: 99%

Towards Intelligent Computer Assisted Educational Role-Play

Lim¹,

Aylett²,

Enz

et al. 2009

Learning by Playing. Game-Based Education System Design and Development

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Abstract. This paper investigates how graphically displayed intelligent virtual actors, mobile devices and innovative interaction modalities can support and enhance educational role-play as well as deepen the sense of engagement and presence in participants to produce more successful learning. The discussion will be presented using a showcase from the eCIRCUS project, ORIENT, an application combining virtual and real life role-play for social and emotional learning.

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“…For instance, it has been shown that empathic virtual humans can reduce stress levels during job interview tasks [17] and that empathic agents are perceived as more likable, trustworthy, and caring [7]. Furthermore, it has been found that empathic virtual humans can evoke empathy in children and can thus teach them to deal with bullying situations [16] and that a virtual human's empathic behavior also contributes to its ability to build and sustain long-term socio-emotional relationships with human partners [3]. However, it has been shown that in a competitive card game scenario, empathic emotions can increase arousal and induce stress in an interaction partner [1].…”

Section: Introductionmentioning

confidence: 99%

Empathy and Its Modulation in a Virtual Human

Boukricha

Wachsmuth

Carminati

et al. 2013

KI 2013: Advances in Artificial Intelligence

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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.

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Learning by Feeling: Evoking Empathy With Synthetic Characters

Cited by 133 publications

References 15 publications

From Non-human to Human: Adult’s and Children’s Perceptions of Agents Varying in Humanness

From Non-human to Human: Adult’s and Children’s Perceptions of Agents Varying in Humanness

Towards Intelligent Computer Assisted Educational Role-Play

Empathy and Its Modulation in a Virtual Human

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