From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications
От больших моделей искусственного интеллекта к агентному ИИ: учебное руководство по интеллектуальным коммуникациям будущего
2026-01-01
SCID: 54.1/u3psf7um
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6G communicationsAgentic AILarge Artificial Intelligence Modelsintelligent communication systemsworld models
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Abstract (AI)
With the advent of 6G communications, intelligent communication systems face multiple challenges, including constrained perception and response capabilities, limited scalability, and low adaptability in dynamic environments. To address these challenges, this tutorial provides a systematic and comprehensive introduction to the principles, design, and applications of Large Artificial Intelligence Models (LAMs) and Agentic AI technologies in intelligent communication systems, aiming to offer researchers an integrated overview of cutting-edge methodologies and practical insights. First, the tutorial outlines the background of 6G communications and reviews the technological evolution from LAMs to Agentic AI. It then systematically examines the key components required for constructing LAMs, classifies various types of LAMs, and analyzes their applicability in communication. A LAM-centric design paradigm tailored for communication systems is subsequently proposed, encompassing dataset construction, internal learning, and external learning approaches. Building upon this foundation, the tutorial develops an LAM-based Agentic AI system for intelligent communications, elaborating on its core components—including agents, world models, planners, knowledge bases, tools, and memory modules— as well as their interaction mechanisms. Finally, it provides an in-depth review of representative applications of LAMs and Agentic AI in communication scenarios, and summarizes the current research challenges and future directions, with the goal of fostering the development of efficient, secure, and sustainable next-generation intelligent communication systems.
Key Findings
1
It develops an LAM-based Agentic AI architecture integrating agents, world models, planners, knowledge bases, tools, and memory modules.
2
It proposes a communication-oriented LAM design paradigm covering dataset construction, internal learning, and external learning.
3
It systematically reviews the evolution from Large Artificial Intelligence Models to Agentic AI and assesses their applicability to communication systems.
4
The tutorial identifies constrained perception and response, limited scalability, and poor adaptability as major challenges for intelligent 6G communication systems.
5
The tutorial surveys representative communication applications and highlights unresolved challenges and future directions for efficient, secure, and sustainable intelligent communications.
Research Object
6G intelligent communication systems incorporating Large Artificial Intelligence Models (LAMs) and Agentic AI
Research Subject
The principles, design, component interactions, applications, scalability, adaptability, efficiency, security, and sustainability of LAM- and Agentic-AI-based communication systems
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2026-01-01
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