对比大模型驱动与传统多智能体系统，揭示技术演进差异
Contemporary Agent Technology: LLM-Driven Advancements vs Classic Multi-Agent Systems
- 以大语言模型重构智能体协作范式
- 新系统在灵活性与可扩展性上优于经典多智能体
- 适合关注AI架构演进的研究者与开发者
本文全面反思当代智能体技术，重点比较由大语言模型（LLM）驱动的新型系统与经典多智能体系统（MAS）的进展。深入探讨定义这些新系统的模型、方法与特性，并批判性分析近期发展与核心学术文献中基础MAS理论之间的关联。最后，识别该快速演变领域中的关键挑战与有前景的未来方向。
原文摘要 · Abstract (English)
This contribution provides our comprehensive reflection on the contemporary agent technology, with a particular focus on the advancements driven by Large Language Models (LLM) vs classic Multi-Agent Systems (MAS). It delves into the models, approaches, and characteristics that define these new systems. The paper emphasizes the critical analysis of how the recent developments relate to the foundational MAS, as articulated in the core academic literature. Finally, it identifies key challenges and promising future directions in this rapidly evolving domain.
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