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.

翻译：实现L4/L5级自主网络（AN）需要从静态自动化向智能体原生智能的范式转变。当前依赖刚性脚本的运维方式缺乏应对非标称条件的认知能力。为此，本快报提出一种实现高级自主性的分层多智能体参考架构。该框架采用双驱动编排器协调专用执行智能体，并由共享公共记忆体实现统一领域知识支撑。关键创新在于集成智能体自我意识，使系统能够协调深思熟虑的战略治理与反射性故障恢复。我们在5G核心网环境中实例化并验证了该架构。案例研究表明，系统能在拥塞条件下维持关键吞吐量，并将平均修复时间（MTTR）降低86%，证实其在统一战略规划与运维韧性方面的有效性。