跳到正文
研踪PaperTrail

YOUR RESEARCH, IN SIGHT

让下一篇重要论文,不再错过。

覆盖计算机全学科,以 AI 为快捷入口。关注方向、作者和关键词,把发现变成持续的研究积累。

采集已暂停
正在读取账号与研究记录…

全站更新概况

+0新增论文
+0其中 AI 相关
+0已有论文修订
+0新增 AI 导读

arXiv 最近完成扫描:等待完成 · 全站最近入库:2026-11-02 00:39各信源进度 →

统计口径与数据新鲜度

统计 2026-11-03 14:39 — 2026-11-04 14:39(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:尚未完成最近发现新增版本:2026-11-02 00:39库内论文最新更新时间:2026-10-30 01:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

8,677 已收录论文7,675 AI 相关1,866 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。

找到 1 篇论文 · 按版本更新时间排序等待首次采集
新论文 · v1arXiv:2610.35978

Testing Agentic Service Systems: An Agentic Living Lab Methodology Across the Physical-Digital Continuum

Zhongjie Wang, Xiang He, Xiao Wang, Mingyi Liu, Shuang Yu, Hanchuan Xu

Task success is insufficient for testing agents that act for principals, change persistent business state, and affect physical processes: a useful result may be unauthorized, leave obligations unresolved, or depend on the execution substrate. We propose an Agentic Living Lab methodology organized around three questions: what is the test unit, who and what participate, and under what reality is the test executed? The unit is a service episode containing delegated roles, obligations, world state, and evidence. The method separates agents under test from environment actors and distinguishes real humans, human traces, rule surrogates, and agent-based proxies. Realization Profiles, capability-declared Reality Substrate bindings, Grounding Profiles, and Semantic Delta disclosures make changes across software, enterprise systems, simulation, and physical settings explicit. A four-plane reference architecture separates experiment control, participants, world realization, and evidence evaluation, with cross-cutting authority and governance controls. Runtime semantics distinguish intent, normative admission, and factual reconciliation. Real stakeholder grounding, participant calibration or validation, and governed feedback are required for the Living Lab claim, but not synchronous human participation in every run. Released JSON Schemas, deterministic fixtures, and a limited reference runner make selected rules machine-checkable; they are not a complete platform or empirical validation. Constructed travel and industrial designs illustrate authorization and fulfillment failures, proxy sensitivity, and substrate changes. Agent quality, proxy validity, and cross-substrate effect stability remain empirical questions.

尚无 AI 解读,展示原文摘要

cs.SE
arXiv ↗PDF ↗