信息通信技术与政策

信息通信技术与政策

信息通信技术与政策 ›› 2026, Vol. 52 ›› Issue (10): 47-54.doi: 10.12267/j.issn.2096-5931.2026.10.006

专题: 6G通智融合 上一篇    下一篇

面向6G核心网的多智能体协同与AI能力生命周期管理架构*

Multi-agent collaboration and AI capability lifecycle management architecture for 6G core networks

李嘉慧, 孙嫣然, 龙彪   

  1. 中国电信股份有限公司研究院核心网技术研究所, 广州 510000
  • 收稿日期:2026-09-10 出版日期:2026-10-25 发布日期:2026-10-28
  • 通讯作者: 龙彪
  • 作者简介:
    李嘉慧,中国电信股份有限公司研究院核心网技术研究所工程师,主要从事移动核心网技术等方面的研究与标准化工作;
    孙嫣然,中国电信股份有限公司研究院核心网技术研究所工程师,主要从事移动核心网技术等方面的研究与标准化工作
  • 基金资助:
    *国家科技重大专项项目(2025ZD1302700)

LI Jiahui, SUN Yanran, LONG Biao   

  1. Core Network Technology Research Department, China Telecom Research Institute, Guangzhou 510000, China
  • Received:2026-09-10 Online:2026-10-25 Published:2026-10-28
  • Contact: LONG Biao

摘要:

6G核心网向内生智能演进已成为业界共识,但现有研究在智能体架构、意图处理与人工智能(Artificial Intelligence,AI)能力管控方面仍呈现碎片化特征。立足于当前6G架构标准化的研究进展,提出了一种面向6G核心网的多智能体协同与AI能力生命周期管理架构。该架构引入规划智能体与执行智能体两类网络级AI智能体,不同智能体之间通过智能体专属接口进行任务级协作;同时架构设置了AI控制功能,可对AI能力注册、模型训练、验证入库、供给部署、运行监测、重训练和异常回退实施统一管控。

关键词: 6G核心网, 服务化架构, AI智能体, 意图驱动, 模型生命周期管理

Abstract:

The evolution of the 6G core network toward endogenous intelligence has become a consensus within the industry. However, existing research still exhibits fragmented characteristics regarding multi-agent architectures, intent processing, and the management of Artificial Intelligence (AI) capabilities. Building upon current advancements in 6G architecture standardization research, this study proposes a multi-agent collaboration and AI capability lifecycle management architecture tailored for 6G core networks. This architecture introduces two types of network-level AI agents, namely planning agents and execution agents, with task-level collaboration among heterogeneous agents implemented through dedicated agent-specific interfaces. Simultaneously, the architecture incorporates AI control functionalities that enable unified management of AI capability registration, model training, validation and database integration, provisioning and deployment, operational monitoring, retraining, and anomaly-based rollback.

Key words: 6G core network, service-oriented architecture, AI agent, intent-driven, model lifecycle management

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