Human-Artificial Interaction in the Age of Agentic AI: A System-Theoretical Approach

• URL: http://arxiv.org/abs/2502.14000v1
• Date: Wed, 19 Feb 2025 07:55:34 GMT
• Title: Human-Artificial Interaction in the Age of Agentic AI: A System-Theoretical Approach
• Authors: Uwe M. Borghoff, Paolo Bottoni, Remo Pareschi,
• Abstract summary: This paper presents a novel perspective on human-computer interaction (HCI), framing it as a dynamic interplay between human and computational agents.<n>A key distinction is made between multi-agent systems (MAS) and Centaurian systems, which represent two different paradigms of human-AI collaboration.<n>Our research has practical applications in autonomous robotics, human-in-the-loop decision making, and AI-driven cognitive architectures.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents a novel perspective on human-computer interaction (HCI), framing it as a dynamic interplay between human and computational agents within a networked system. Going beyond traditional interface-based approaches, we emphasize the importance of coordination and communication among heterogeneous agents with different capabilities, roles, and goals. A key distinction is made between multi-agent systems (MAS) and Centaurian systems, which represent two different paradigms of human-AI collaboration. MAS maintain agent autonomy, with structured protocols enabling cooperation, while Centaurian systems deeply integrate human and AI capabilities, creating unified decision-making entities. To formalize these interactions, we introduce a framework for communication spaces, structured into surface, observation, and computation layers, ensuring seamless integration between MAS and Centaurian architectures, where colored Petri nets effectively represent structured Centaurian systems and high-level reconfigurable networks address the dynamic nature of MAS. Our research has practical applications in autonomous robotics, human-in-the-loop decision making, and AI-driven cognitive architectures, and provides a foundation for next-generation hybrid intelligence systems that balance structured coordination with emergent behavior.

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