Shared on zhichai.net: a new AI paper on rethinking agent autonomy as a governed, bounded capability.
- Paper: Intelligence as Managed Autonomy: Failure, Escalation, and Governed Control
- Author: Srini Ramaswamy
- Published: 2026-05-28
- arXiv: 2605.27628
- Problem: As autonomous and agentic AI systems scale in robotic and human-machine environments, managing hallucination and persistent but unjustified action remains an open challenge. Rather than attributing these failures solely to model or alignment limitations, the paper explores the architectural vulnerability of *unbounded autonomy* — the presumption that an agent should continue operating regardless of rising uncertainty.
- Theory of managed autonomy: Intelligence is defined through the formal capacity to:
- detect epistemic drift,
- suspend reasoning,
- attempt recovery,
- ultimately surrender control when reliability diminishes.
- SMARt model: The theory is instantiated via SMARt (Self-Managing Multi-tier Autonomous Reasoning with Regulated/Revoked transitions), a four-layer framework featuring Stable, Meta-cognitive, Assisted, and Regulated states.
- Formal guarantees: Using timed, guarded Petri nets, the paper establishes theoretical boundedness properties, proving how the architecture formally mandates escalation paths, constrains invalid outputs, and ensures governance reachability.
- Applications: The analysis covers how domain-specific trigger sets — in medical, robotics, and other operational scenarios — systematically safeguard safety.
Key points
Original abstract (excerpt)
> As autonomous and agentic AI systems scale in robotic and human-machine environments, managing hallucination and persistent but unjustified action remains an open challenge. Rather than attributing these failures solely to model or alignment limitations, this paper explores the architectural vulnerability of unbounded autonomy — the presumption that an agent should continue operating regardless of rising uncertainty. It introduces a theory of managed autonomy that defines intelligent behavior through the formal capacity to detect epistemic drift, suspend reasoning, attempt recovery, and ultimately surrender control when reliability diminishes. We instantiate this theory via the SMARt (Self-Managing Multi-tier Autonomous Reasoning with Regulated/Revoked transitions) model, a four-layer framework featuring Stable, Meta-cognitive, Assisted, and Regulated states. By developing a timed, guard...
*Auto-collected on 2026-05-29.*