发表机构
EURECOM; University of Sharjah（EURECOM; 谢贾学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究5G/6G网络中基于大语言模型的智能体人工智能，通过分为两部分的教程与综述，形式化5G和6G相关平面，涵盖智能体系统基础，映射其能力到控制面等，识别自主电信面临的开放挑战。
AI 中文摘要
由大语言模型驱动的智能体人工智能标志着从基于规则的自动化向对下一代网络进行自主、目标驱动控制的转变。现有综述孤立地对待这两个领域，对协议集成、评估和标准化对齐的探索不足。为填补这一空白，本文给出了一个分为两部分的教程与综述。第一部分对5G和6G的控制、管理及人工智能原生平面进行形式化，接着涵盖智能体系统的基础：推理、规划、工具使用、多智能体协调和评估。第二部分将智能体能力映射到5G/6G控制面、标准化及主要的6G计划上。最后，识别出塑造自主电信的开放挑战。
英文摘要
Agentic Artificial Intelligence (AI), enabled by Large Language Models, marks a shift from rule-based automation toward autonomous, goal-driven control of Next-Generation Networks (NGNs). Existing surveys treat the two domains in isolation, leaving protocol integration, evaluation, and standardization alignment underexplored. To address this gap, a two-part tutorial-and-survey is presented. Part I formalises the control, management, and AI-native planes of 5G and 6G. It then covers the foundations of agentic systems: reasoning, planning, tool use, multi-agent coordination, and evaluation. Part II maps agentic capabilities onto 5G/6G control surfaces, standardization, and major 6G initiatives. Finally, it identifies open challenges shaping autonomous telecommunications.
Comments35 pages, 4 figures, Under review
