用大模型构建可解释的网络数字孪生，迈向自适应通信网络
Hermes: A Large Language Model Framework on the Journey to Autonomous Networks
- 设计多智能体链式架构，通过蓝图实现结构化网络建模
- 支持多种场景配置的自动建模，提升网络自治能力
- 适合通信系统自动化研究者与智能运维工程师
随着通信网络复杂度提升，自动化运营需求日益迫切。尽管已有进展，但完全自主仍受限于人工建模与策略制定。网络数字孪生（NDTs）有望增强网络智能，但其应用受制于特定场景架构，难以推动全面自治。为此，本文提出Hermes框架，基于大语言模型（LLMs）构建多智能体链，利用“蓝图”实现结构化、可解释的数字孪生实例构建。该框架可自动、可靠、准确地建模多样化网络用例与配置，显著推进全自主网络运营进程。
原文摘要 · Abstract (English)
The drive toward automating cellular network operations has grown with the increasing complexity of these systems. Despite advancements, full autonomy currently remains out of reach due to reliance on human intervention for modeling network behaviors and defining policies to meet target requirements. Network Digital Twins (NDTs) have shown promise in enhancing network intelligence, but the successful implementation of this technology is constrained by use case-specific architectures, limiting its role in advancing network autonomy. A more capable network intelligence, or "telecommunications brain", is needed to enable seamless, autonomous management of cellular network. Large Language Models (LLMs) have emerged as potential enablers for this vision but face challenges in network modeling, especially in reasoning and handling diverse data types. To address these gaps, we introduce Hermes, a chain of LLM agents that uses "blueprints" for constructing NDT instances through structured and explainable logical steps. Hermes allows automatic, reliable, and accurate network modeling of diverse use cases and configurations, thus marking progress toward fully autonomous network operations.
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