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arXiv AI By Tianzhu Zhang, Chih-Kai Huang, Meikang Qiu

Can AI Agents Deliver Verifiable Network-Wide Outcomes Across Authority Boundaries?

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The paper introduces EvidenceNet, a runtime assurance layer designed to verify that coordinated AI agent operations achieve an operator’s intended network-wide outcomes across multiple administrative domains. EvidenceNet collects post-change observations from the required authority scopes, checks their freshness and validity, and uses a verifier agent to assess observation content. Experiments on live routing networks demonstrate that this approach can detect successful outcomes that configuration-action logs alone miss, and it rejects completions when observations are sourced incorrectly, substituted, or stale.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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