标题： 从语义网络和MAS到代理AI：代理网络的统一叙述 显示英文标题

标题： From Semantic Web and MAS to Agentic AI: A Unified Narrative of the Web of Agents

摘要： 网络代理概念（WoA）将静态的、以文档为中心的网络转变为由自主代理代表用户行动的环境，随着大型语言模型（LLMs）能力的增强，这一概念引起了越来越多的关注。 然而，该领域的研究仍分散在不同的社区中。 当代的综述列出了最新的LLM驱动的框架，而多代理系统（MAS）和语义网的丰富历史往往被视为独立的、过时的领域。 这种碎片化掩盖了现代系统的知识传承，并阻碍了对领域发展轨迹的全面理解。 我们提出了第一个全面的WoA演化概述。 我们表明，现代协议如A2A和MCP，是对早期标准如FIPA标准和基于OWL的语义代理的已 documented 限制的直接进化反应。 为了系统化这一分析，我们引入了一个四轴分类法（语义基础、通信范式、智能定位、发现机制）。 这个框架为比较所有代际的代理架构提供了一个统一的分析视角，揭示了一条清晰的传承线，而其他人则看到了断层。 我们的分析识别了“智能定位”的范式转变：从编码在外部数据（语义网）或平台（MAS）中，到嵌入在代理的核心模型（LLM）中。 这一转变是现代代理人工智能的基础，使WoA长期以来设想的可扩展和自适应系统成为可能。 我们得出结论，尽管新协议至关重要，但它们对于构建一个强大、开放、值得信赖的生态系统是不够的。 最后，我们认为下一个研究前沿在于解决持续的社会技术挑战，并我们勾勒出一个专注于去中心化身份、经济模型、安全性和治理的新议程，针对新兴的WoA。 显示英文摘要

摘要： The concept of the Web of Agents (WoA), which transforms the static, document-centric Web into an environment of autonomous agents acting on users' behalf, has attracted growing interest as large language models (LLMs) become more capable. However, research in this area is still fragmented across different communities. Contemporary surveys catalog the latest LLM-powered frameworks, while the rich histories of Multi-Agent Systems (MAS) and the Semantic Web are often treated as separate, legacy domains. This fragmentation obscures the intellectual lineage of modern systems and hinders a holistic understanding of the field's trajectory. We present the first comprehensive evolutionary overview of the WoA. We show that modern protocols like A2A and the MCP, are direct evolutionary responses to the well-documented limitations of earlier standards like FIPA standards and OWL-based semantic agents. To systematize this analysis, we introduce a four-axis taxonomy (semantic foundation, communication paradigm, locus of intelligence, discovery mechanism). This framework provides a unified analytical lens for comparing agent architectures across all generations, revealing a clear line of descent where others have seen a disconnect. Our analysis identifies a paradigm shift in the 'locus of intelligence': from being encoded in external data (Semantic Web) or the platform (MAS) to being embedded within the agent's core model (LLM). This shift is foundational to modern Agentic AI, enabling the scalable and adaptive systems the WoA has long envisioned. We conclude that while new protocols are essential, they are insufficient for building a robust, open, trustworthy ecosystem. Finally, we argue that the next research frontier lies in solving persistent socio-technical challenges, and we map out a new agenda focused on decentralized identity, economic models, security, and governance for the emerging WoA.