Managed Autonomy Framework for Agentic AI Systems
A recent study published on arXiv (2605.27628) presents a theory of managed autonomy for agentic AI systems, viewing hallucinations and unwarranted actions not merely as flaws in the model but as structural weaknesses stemming from unrestricted autonomy. The researchers propose the SMARt (Self-Managing Multi-tier Autonomous Reasoning with Regulated/Revoked transitions) framework, which consists of four layers: Stable, Meta-cognitive, Assisted, and Regulated states. This theory characterizes intelligent behavior as the ability to recognize epistemic drift, pause reasoning, attempt to recover, and relinquish control when reliability wanes. Additionally, a timed, guarded Petri net formulation lays the groundwork for governance in autonomous systems.
Key facts
- Paper arXiv:2605.27628 proposes theory of managed autonomy for agentic AI
- Addresses hallucination and unjustified actions as architectural vulnerabilities
- Introduces SMARt model with four layers: Stable, Meta-cognitive, Assisted, Regulated
- Defines intelligent behavior as detecting epistemic drift and surrendering control
- Uses timed, guarded Petri net formulation for theoretical grounding
- Focuses on scaling in robotic and human-machine environments
- Challenges attribution of failures solely to model or alignment limitations
- Proposes governance mechanism for autonomous systems
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Institutions
- arXiv