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Taming the Agentic RAN: Stability-Guaranteed Arbitration of Autonomous AI Agents in O-RAN

Paper recorded by Signals 4 on 2026-09-16 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17

Category: cs.AI · 人工智能 · first seen 2026-09-17

Abstract

The O-RAN control plane is becoming agentic: autonomous AI agents, deployed as rApps by different vendors, independently close control loops over shared radio resources. We demonstrate on a live O-RAN system that this independence is unsafe. Two agents with individually correct objectives, one protecting a latency SLA and one maximizing utilization for energy efficiency, jointly drive recurring op

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#40 most recent of 300 cs.AI papers we have recorded · ↑ newer: Decodable but Misrouted: Sparse Features Uncover a Readout Gap in Visi · ↓ older: Agentic Societies Need a Social Harness
Cite this page: Taming the Agentic RAN: Stability-Guaranteed Arbitration of Autonomous AI Agents in O-RAN: the #40 most recent of 300 cs.AI papers we have recorded (as of 2026-09-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/taming-the-agentic-ran-stability-guaranteed-arbitration-of-autonomous-ai-agents-.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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