Abstract
The fields of human-robot interaction (HRI) and embodied conversational agents (ECAs) have long studied how empathy could be implemented in machines. One of the major drivers has been the goal of giving multimodal social and emotional intelligence to these artificially intelligent agents, which interact with people through facial expressions, body, gesture, and speech. What empathic behaviors and models have these fields implemented by mimicking human and animal behavior? In what ways have they explored creating machine-specific analogies? This chapter aims to review the knowledge from these studies, towards applying the lessons learned to today's ubiquitous, language-based agents such as ChatGPT.
Abstract (translated)
人机交互（HRI）与具身智能体（ECAs）领域长期以来一直研究如何在机器中实现共情。其主要目标之一是为这些通过面部表情、身体动作、手势和语音与人交互的人工智能体赋予多模态社交与情感智能。这些领域通过模仿人类与动物行为，实现了哪些共情行为与模型？它们又以何种方式探索了创造机器特有的类比？本章旨在回顾这些研究的成果，从而将经验应用于当今无处不在的语言模型（如ChatGPT）。
URL
https://arxiv.org/abs/2603.20200
