Affective Communication via Active Inference
2024年1月1日
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1 min read
Based on active inference and the free-energy principle, we computationally model multimodal affective communication between robots and humans. Integrating energy-minimization-driven active perception by the robot with emotion estimation and expression through mental simulation, we build frameworks in which the robot reads and responds to others’ emotions.
Related papers:
- Takato Horii, Yukie Nagai. “Active Inference through Energy Minimization in Multimodal Affective Human-Robot Interaction”. Frontiers in Robotics and AI, 2021.
- Takato Horii, Yukie Nagai, Minoru Asada. “Imitation of Human Expressions Based on Emotion Estimation by Mental Simulation”. Paladyn, Journal of Behavioral Robotics, 7(1), 40-54, December 2016.
- Yukie Nagai, Takato Horii. “Computational Model of Emotion Based on Predictive Learning” (in Japanese). Journal of the Japanese Society for Artificial Intelligence, 31(5), 694-701, September 2016.
- Takato Horii. “Toward Constructive Understanding of Emotion through Bodily and Social Interactions” (in Japanese). Baby Science, 24: 46-57, 2025.
Authors
Takato Horii
(he/him)
Associate Professor
Associate Professor at Graduate School of Engineering Science, Osaka University.
Research interests include cognitive developmental robotics, computational modeling
of emotional development, and human-robot interaction.