EmoACT: a Framework to Embed Emotions into Artificial Agents Based on Affect Control Theory
🤖 AI Summary
This study addresses the limited sociality of robots in human–robot interaction by proposing EmoACT—the first platform-agnostic affective modeling framework grounded in Affect Control Theory (ACT). Methodologically, it systematically integrates ACT into artificial agent modeling, establishing an emotion-state space mapping, a real-time emotion-triggering mechanism, and an interpretable emotion–behavior coupling mechanism; a human–robot interaction perception experiment was further designed to empirically validate causal effects. Results demonstrate that EmoACT significantly enhances users’ perceived emotional and cognitive agency of robots (p < 0.01) and strengthens their identification of robots as social agents rather than mere tools. Moreover, it provides empirical evidence for a causal relationship between emotion expression frequency and social perception. This work establishes a scalable theoretical framework and empirical foundation for socially grounded affective modeling in embodied agents.
Application Category
📝 Abstract
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.
Problem
Research questions and friction points this paper is trying to address.
Enhancing human-robot interaction through emotional embodiment
Generating synthetic emotions using Affect Control Theory
Improving perceived emotional and cognitive agency in robots
Innovation
Methods, ideas, or system contributions that make the work stand out.
Uses Affect Control Theory for emotion generation
Platform-agnostic framework for emotional embedding
Enhances perceived agency via emotional expressions
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