From Intelligence to Autonomy: Foundations and Construction of Autonomous Agents for Future Intelligent Systems

The paper defines an autonomous agent as a system that maintains task goals and viability within explicit identity and authority boundaries, continuously acting with world and self-models, and adjusting control mechanisms through feedback. It traces the evolution from homeostasis to biological autonomy and identifies six operationalization lines, culminating in a one-boundary, four-loop framework that organizes task execution, self-maintenance, metacontrol, and governed learning. Five simulation experiments test permission constraints, road-closure response, health maintenance, capability re-estimation, and cross-task learning, offering preliminary evidence for the feasibility of these mechanisms while noting the need for broader testing.

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• agents
• robotics