用情绪控制理论让机器人自然表达情感，提升人机互动体验
EmoACT: a Framework to Embed Emotions into Artificial Agents Based on Affect Control Theory
- 基于情绪控制理论构建通用情感框架
- 情感表达频率影响用户对机器人的感知
- 适合希望提升机器人社交性的开发者
随着机器人日益融入日常生活，提升其与人类的交互能力至关重要。情绪在人类互动中起关键作用，若能将情绪嵌入人工代理，可增强人机交互的自然性与透明度。本研究采用扎根于互动的心理学模型——情绪控制理论（Affect Control Theory, ACT），构建一种平台无关的情感生成框架，并在类人机器人上实现，评估其对人类感知的影响。结果表明，情感表现频率显著影响用户对机器人的认知；适当的情感表达可增强机器人在情感与认知层面的代理感。研究证明，ACT可有效用于在机器人中嵌入合成情绪，实现更接近社会代理而非单纯机器的人机交互。
原文摘要 · Abstract (English)
As robots and artificial agents become increasingly integrated into daily life, enhancing their ability to interact with humans is essential. Emotions, which play a crucial role in human interactions, can improve the naturalness and transparency of human-robot interactions (HRI) when embodied in artificial agents. This study aims to employ Affect Control Theory (ACT), a psychological model of emotions deeply rooted in interaction, for the generation of synthetic emotions. A platform-agnostic framework inspired by ACT was developed and implemented in a humanoid robot to assess its impact on human perception. Results show that the frequency of emotional displays impacts how users perceive the robot. Moreover, appropriate emotional expressions seem to enhance the robot's perceived emotional and cognitive agency. The findings suggest that ACT can be successfully employed to embed synthetic emotions into robots, resulting in effective human-robot interactions, where the robot is perceived more as a social agent than merely a machine.
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