When the Governor Becomes the Disturbance: Control-Generated Disturbance and Cost-Aware Backoff in Governed Tool-Using Agents
3.80T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2610.09037.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryA study of supervisory governors overseeing tool-using AI agents, finding that cost-blind governors can convert tool failures into persistent blocking that prevents task completion. An adaptive backoff rule reducing intervention probability using a moving average of induced events improves completion in a controlled file-recovery environment, tested on a hand-coded agent and Gemini 2.5 Flash across 576 episodes.
Why it mattersNames a concrete failure mode where oversight mechanisms themselves block the agents they supervise, and tests an explicit mitigation. Directly relevant to designing supervisor loops around tool-using agents.
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