综述大模型驱动的多智能体系统，梳理应用与未来方向
A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application
- 构建统一框架归纳大模型多智能体系统
- 涵盖复杂任务求解、场景模拟与生成智能体评估
- 适合关注AI协作与智能体系统的研究人员
基于大语言模型的多智能体系统（LLM-MAS）自大模型兴起以来成为研究热点。然而，随着新成果不断涌现，现有综述难以全面覆盖。本文对相关研究进行全面梳理，首先明确LLM-MAS的定义，整合已有工作；接着从三方面概述其应用：解决复杂任务、模拟特定场景、评估生成式智能体；在此基础上，总结当前面临挑战，并提出该领域未来的研究方向。
原文摘要 · Abstract (English)
LLM-based Multi-Agent Systems ( LLM-MAS ) have become a research hotspot since the rise of large language models (LLMs). However, with the continuous influx of new related works, the existing reviews struggle to capture them comprehensively. This paper presents a comprehensive survey of these studies. We first discuss the definition of LLM-MAS, a framework encompassing much of previous work. We provide an overview of the various applications of LLM-MAS in (i) solving complex tasks, (ii) simulating specific scenarios, and (iii) evaluating generative agents. Building on previous studies, we also highlight several challenges and propose future directions for research in this field.
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