构建分层智能体架构，让网络自主应对异常并快速恢复。
From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)
- 用分层智能体+共享记忆实现网络自主决策
- 在5G核心网中使故障修复时间缩短86%
- 适合需要高可靠自治的通信系统研发者
实现4/5级自治网络（AN）需从静态自动化转向原生智能体架构。现有运维依赖僵化脚本，缺乏应对异常情况的认知能力。本文提出一种分层多智能体参考架构，通过双驱编排器协调专用执行智能体，并依托共享公共记忆提供统一领域知识。关键创新在于引入智能体自我意识，使系统能协同战略规划与实时故障恢复。在5G核心网环境中实例化并验证该架构。案例研究表明，系统在拥塞下仍维持关键吞吐量，平均故障修复时间（MTTR）降低86%，证实其在战略规划与运行韧性统一上的有效性。
原文摘要 · Abstract (English)
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.
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