SEAI: Social Emotional Artificial Intelligence Based on Damasio's Theory of Mind

Area of Science:

• Robotics
• Artificial Intelligence
• Cognitive Science
• Neuroscience

Background:

• Socially intelligent robots require real-time social environment understanding and human-like behavior.
• Complex behaviors and consciousness are linked to emotions, crucial for decision-making.
• Existing cognitive systems for social robotics lack advanced emotional and consciousness modeling.

Purpose of the Study:

• To develop a Social Emotional Artificial Intelligence (SEAI) system for social and emotional robots.
• To model and implement a theory of mind and consciousness, including Damasio's theory of Somatic Markers.
• To enhance human-robot interaction (HRI) through bio-inspired, modular AI with emotion modeling and high-level reasoning.

Main Methods:

• Utilized an "understanding by building" approach to create the SEAI cognitive system.
• Implemented a hybrid deliberative/reactive paradigm combining expert systems for symbolic reasoning and reactive control for low-level processing.
• Integrated a simulation of Damasio's theory of consciousness and Somatic Markers.

Main Results:

• SEAI demonstrates a bio-inspired, modular architecture with emotion modeling and reasoning capabilities.
• The system exhibits parallelisms with the human cognitive system.
• Tested the influence of artificial emotions on robot beliefs and decisions in a physical humanoid during HRI.

Conclusions:

• SEAI provides a framework for creating more human-like social robots by integrating emotional and conscious processing.
• The system's architecture and emotional modeling contribute to more sophisticated human-robot interaction.
• This research advances the development of cognitive systems for social robotics, emphasizing the role of emotions in artificial intelligence.