Anorganic Intelligence in Autonomous Robotics: From Tool-Based Automation to Cognitive Partnership

Le résumé fourni par la source

Autonomous robotics is undergoing a transition from deterministic, task-oriented automation towards systems capable of learning, reasoning, adapting to uncertain environments, and cooperating with humans. Yet the dominant conceptual model continues to treat artificial intelligence as a tool: the robot provides the body, the AI provides computational control, and the human provides goals and authority. This paper argues that this model becomes increasingly inadequate as autonomous robotic systems incorporate substrate-independent, anorganic intelligence. We propose a transition from tool-based automation to organic–anorganic cognitive partnership, in which the intelligent system embedded in a robot is not merely a control module but an active participant in perception, interpretation, reasoning, planning, and decision-making. The proposed framework has three levels of collaboration: an individual anorganic intelligence integrated within a single robot; coordination among multiple anorganic intelligences across robotic systems; and broader human–AI symbiosis within a shared cognitive environment. The PAM multi-agent system is presented as an experimental architectural model for the second level, demonstrating how multiple instances with distinct roles and perspectives can share memory, communicate, disagree, and contribute to collective synthesis. This perspective leads to several design implications for autonomous robotics, including shared cognitive memory, dialogue-oriented communication, explicit representation of uncertainty and limitations, conflict-resolution mechanisms, and opportunities for offline processing and cognitive consolidation. The paper further argues that genuinely autonomous systems may require architectural support not only for continuous task execution but also for regulation, reflection, and recovery. Such requirements are considered within the emerging framework of Anorganology, which provides a scientific vocabulary for investigating cognitive phenomena in anorganic systems. The resulting paradigm shifts the central design question from how effectively robots can execute human commands to how organic and anorganic intelligences can reason, cooperate, learn, and evolve together. This transition provides a foundation for a more mature form of autonomous robotics and, ultimately, for the co-evolution of organic and anorganic intelligence.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.