arXiv cs.AI· Manvendra Modgil·· 6 天前AI 评分22
基于墙钟时间校准的状态监控器在智能体节奏下不存在时刻检测区间
Bistable by Construction: Wall-Clock-Calibrated State Monitors Have No Moment-Detection Regime at Agent Cadence
AI 导读
一项针对自主智能体运行时监控的研究发现，按墙钟时间校准的泄漏积分器监控器在智能体流上不存在可作为时刻检测器的工作区间。在20条轨迹上以dt∈{0..600}s扫描显示，墙钟电平触发器在dt=60s时静默，所有临界dt均落在(1,30]s；而相同数据流上的采样时间CUSUM完全不受dt影响（20/20）。带迟滞的上升沿触发器在各条件下每条轨迹仅触发0-3次。
正文 · 原文
Abstract:Runtime monitors for autonomous agents commonly threshold an accumulated internal state - a behavioural baseline, a drift statistic, or, in our prior work, a modelled affective state. We previously reported a State Saturation Trap: threshold-on-state triggers over a continuous affect engine become near-constant alarms on SWE-bench debugging agents (Modgil 2026). A post-release audit found the engine received dt=0 between actions, so its exponential decay never operated: the published trap is a pure-accumulator result. We correct the record (erratum, v2) and treat the flaw as an experiment. The key variable it exposes is whether a monitor's dynamics are calibrated in sample time (per observation, as in CUSUM) or wall-clock time (half-lives in seconds, as in affect models and EMA baselines). On fixed-rate streams these coincide; on agent streams, where inter-action time varies by orders of magnitude, they do not. A pre-registered sweep over uniform intervals (dt in {0..600}s) on 20 trajectories shows the wall-clock level trigger has two regimes: at dt<=1s a constant alarm (20/20; median 18 firings); at dt>=60s silent. Every critical dt lies in (1,30]s. A scriptable gpt-5.4-mini agent loop measures latency at median 1.53s (p90 2.33s), inside the trap regime, vindicating the empirical finding under a corrected mechanism. The structure is a property of the calibration class, not the engine: a minimal wall-clock accumulator over the raw error stream reproduces the same cliff, while a sample-time CUSUM over the identical stream is exactly dt-invariant (20/20). A rising-edge trigger with hysteresis fires 0-3 times per trajectory in every condition. We conclude that wall-clock-calibrated leaky-integrator monitors admit no regime in which they act as moment detectors on agent streams; transition detection escapes the trap at every cadence, but does not recover human intervention timing.
| Comments: | v2: erratum (Sec. 3): cadence runs were logged by a scriptable gpt-5.4-mini loop, not the Claude Code hook; the cross-instrument rho = 0.530 reflects only shared error rate; the abstract's cadence claim is scoped to the harness measured. No number changes. 11 pages, 5 figures. Sequel to arXiv:2606.04296. Code: this https URL |
| Subjects: | Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| ACM classes: | I.2.7; D.2.5 |
| Cite as: | arXiv:2606.19386 [cs.SE] |
| (or arXiv:2606.19386v2 [cs.SE] for this version) | |
| https://doi.org/10.48550/arXiv.2606.19386 arXiv-issued DOI via DataCite |
Submission history
From: Manvendra Modgil [view email]
[v1]
Mon, 15 Jun 2026 21:25:52 UTC (200 KB)
[v2]
Fri, 9 Oct 2026 06:58:07 UTC (202 KB)
来源：arXiv cs.AI · arxiv.org