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arXiv:cs.AI· Fouad Bousetouane·· 6 小时前AI 评分37

EIO-Agents:为 AI 智能体评估补上缺失的语义层

EIO-Agents: The Missing Semantic Layer for AI Agent Evaluation

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EIO-Agents 是一个面向可互操作 AI 智能体评估的开放规范,由语义层 EIO 与评估记录 PER 两层构成。EIO 通过类型化证据、版本化行为谓词、证据契约、声明、见证规则、证明状态与可计算推导,为指标、发现、控制项及 PASS、REVIEW、BLOCK 决策提供语义契约;PER 则以内容寻址的规范化表示保存从证据到决策的链路,支持重新推导、解释与验证。该规范共 32 页、11 张图。

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Abstract:AI agents are entering production in increasingly consequential environments without a shared semantic standard for what their evaluations actually mean. Scores, traces, judge outputs, and multi juror findings are increasingly used to justify readiness and release decisions, yet they often do not specify what evidence supports a claim, what that evidence can establish, or how the claim leads to a decision. We introduce EIO-Agents, an open specification for interoperable AI agent evaluation built on two layers. The Evaluation Intelligence Ontology (EIO) provides the semantic layer through typed evidence, versioned behavioral predicates, evidence contracts, claims, witness rules, proof status, recurrence, and computable derivations for metrics, findings, controls, and PASS, REVIEW, or BLOCK decisions. The Portable Evaluation Record (PER) provides the system of record: a canonical, content addressed representation of one evaluation that preserves the evidence to decision chain and can be re derived, explained, and verified. Scores summarize, juries interpret, and traces record, but none of them define what the evidence means or what it can prove. EIO provides that missing semantic contract, while PER preserves the resulting evaluation as a portable and verifiable system of record. As AI agents assume greater operational responsibility, evaluation must become more than a collection of scores and verdicts; it must become an accountable artifact whose meaning, evidence, limitations, and decisions can be independently checked.
Comments: 32 pages, 11 figures
Subjects: Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)
Cite as: arXiv:2610.07675 [cs.AI]
  (or arXiv:2610.07675v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2610.07675

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Fouad Bousetouane [view email]
[v1] Tue, 6 Oct 2026 03:10:53 UTC (2,996 KB)

来源:arXiv:cs.AI · arxiv.org