Computational Models of Consciousness-Emotion Interactions in Robotics
How can robots integrate consciousness and emotions to improve human-robot interaction? This paper by Remigiusz Szczepanowski and colleagues explores computational frameworks for modeling consciousness-emotion (C-E) interactions, drawing insights from neurobiology and machine consciousness to inform social robotics.
Computational Models of Consciousness-Emotion Interactions in Social Robotics: Conceptual Framework, authored by Remigiusz Szczepanowski, Małgorzata Gakis, Krzysztof Arent, and Janusz Sobecki, presents a detailed exploration of how C-E interactions can be computationally modeled and implemented into social robots to improve human-robot interactions.
Key Highlights
- C-E Interaction Framework: Proposes a computational architecture inspired by neurobiological processes, integrating cognition and emotion for enhanced robot behavior.
- Signal-Detection Theory (SDT): Introduces SDT as a quantitative approach to measure and simulate consciousness-emotion interactions in robots.
- Application in Social Robotics: Demonstrates how global processing and hierarchical models of consciousness can enhance the robot’s ability to detect, process, and respond to human emotions effectively.
Connection to ACM
The Artificial Consciousness Module (ACM) aligns with this framework through:
- Integration of Consciousness and Emotions: ACM’s design can incorporate SDT-based models to simulate affective responses and consciousness.
- Quantitative Approaches: The use of computational correlates of consciousness complements ACM’s data-driven architecture for simulating cognitive-emotional interactions.
- Ethical Human-Robot Interaction: Insights from this paper can enhance ACM’s ability to engage in socially intuitive and ethically guided interactions.
For a detailed exploration of the computational models and methodologies discussed, access the full paper here.
