Cognitive Developmental Robotics | Takato Horii | Osaka University

Human–AI Symbiosis and Co-Creation: Self Mirroring Twins for Active Social Co-Creation

Wed, 01 Oct 2025 00:00:00 +0000

This project builds an AI system foundation that enables active social co-creation by having humans live in symbiosis with “Self Mirroring Twins” — agents that learn and imitate the user’s behavior, preferences, and values — thereby deepening self-understanding and prompting behavior change.

Drawing on cognitive developmental robotics and active inference, we model long-term interactions between Self Mirroring Twins and humans, the dynamics by which both parties update their beliefs and predictions, and the computational understanding of how the boundary between the self and the Twin is formed. We aim to demonstrate, on real-world robots and dialogue systems, the effects on behavior change brought about through interaction with the Twin.

Comforting Social Touch — Individual Differences and Cognitive-Scientific Understanding

Tue, 01 Apr 2025 00:00:00 +0000

Being touched by another — stroking, gentle contact, or a handshake — gives us a strong sense of comfort and security. Yet the neural and cognitive mechanisms that underlie this pleasantness, and the origins of individual differences in how it is felt, remain largely unclear.

This project combines psychophysics, neuroscience measurement, and computational modeling to systematically clarify the affective value generated by social touch and its individual differences. Drawing on affective human-robot interaction via touch, we build computational frameworks based on active inference and generative models, and aim at a foundation that allows robots to adaptively respond to individual tactile preferences.

Elucidating Infant Learning Principles Based on Predictive Coding

Mon, 01 Apr 2024 00:00:00 +0000

Human infants acquire the structure of the world and the intentions of others remarkably quickly from limited experience. This project aims to formulate the principles of infant learning as computational models grounded in predictive coding and active inference.

We model the integration of multimodal sensory information and the generative processes of expectations and prediction errors in social interactions with caregivers. From the perspective of cognitive developmental robotics, we bridge real-robot experiments and developmental psychology experiments. By describing infant learning principles as a reproducible computational theory, we aim to apply these insights to the understanding of developmental disorders and to early-learning algorithms for robots.

Computational Modeling of Emotional Development

Mon, 01 Jan 2024 00:00:00 +0000

This line of research computationally models how human emotions develop through multimodal perception (vision, audition, touch). We focus on tactile dominance in infant-caregiver interaction and reproduce the developmental process of emotion perception using probabilistic generative models. We also investigate affective human-robot interaction based on an energy minimization framework grounded in Active Inference.

Cognitive Developmental Robotics | Takato Horii | Osaka University

Human–AI Symbiosis and Co-Creation: Self Mirroring Twins for Active Social Co-Creation

関連する研究費

Comforting Social Touch — Individual Differences and Cognitive-Scientific Understanding

関連する研究費

Elucidating Infant Learning Principles Based on Predictive Coding

関連する研究費

Computational Modeling of Emotional Development