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arXiv 提交日期: 2026-05-20
📄 Abstract - From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)

Realizing Level 4/5 Autonomous Networks (AN) demands a shift from static automation to agent-native intelligence. Current operations, reliant on rigid scripts, lack the cognitive agency to handle off-nominal conditions. To address this, this letter proposes a hierarchical multi-agent reference architecture enabling high-level autonomy. The framework features a Dual-Driven Orchestrator that coordinates specialized Executive Agents, supported by a shared Public Memory for unified domain knowledge. A key innovation is the integration of agent self-awareness, which empowers the system to harmonize deliberative strategic governance with reflexive fault recovery. We instantiate and validate this architecture within a 5G Core environment. Case studies demonstrate that the system sustains critical throughput under congestion and reduces Mean Time to Repair (MTTR) by 86%, confirming its efficacy in unifying strategic planning with operational resilience.

顶级标签: agents systems
详细标签: autonomous networks hierarchical multi-agent self-awareness 5g core fault recovery 或 搜索:

从自动化到自主化:面向智能体原生的分层网络架构(HANA) / From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)


1️⃣ 一句话总结

本文提出了一种名为HANA的分层多智能体网络架构,通过双驱动编排器和共享公共内存,让不同专长的AI智能体协同工作,并在5G核心网中验证,该系统既能像人类专家一样进行战略规划,又能自动应对网络故障,将故障修复时间缩短了86%。

源自 arXiv: 2605.20608