将传统多智能体系统与现代大模型结合，构建去中心化可信协作架构。
Fetch.ai: An Architecture for Modern Multi-Agent Systems
- 基于区块链实现身份验证与交易可追溯的去中心化底层
- 通过原生大模型将人类目标转化为多智能体协同任务流程
- 适用于需安全协作的开放经济生态，如分布式物流系统
近年来以大语言模型驱动的智能系统，大多忽视了数十年来多智能体系统（MAS）的研究基础，导致现有框架存在中心化、信任与通信机制不足等关键缺陷。本文提出 Fetch.ai 架构，一个工业级平台，旨在融合经典 MAS 原则与现代人工智能能力。该架构建立在基于链上区块链服务的去中心化基础之上，支持可验证的身份、发现与交易。同时提供完整的开发框架以创建安全、可互操作的智能体，配套云部署平台及智能编排层——其中原生大模型将高层人类目标转化为复杂的多智能体工作流。我们通过一个去中心化物流用例展示了系统的实际部署能力：自主智能体能动态发现、协商并安全交易。最终，Fetch.ai 堆栈为迈向开放、协作且经济可持续的多智能体生态系统提供了原则性架构。
原文摘要 · Abstract (English)
Recent surges in LLM-driven intelligent systems largely overlook decades of foundational multi-agent systems (MAS) research, resulting in frameworks with critical limitations such as centralization and inadequate trust and communication protocols. This paper introduces the Fetch.ai architecture, an industrial-strength platform designed to bridge this gap by facilitating the integration of classical MAS principles with modern AI capabilities. We present a novel, multi-layered solution built on a decentralized foundation of on-chain blockchain services for verifiable identity, discovery, and transactions. This is complemented by a comprehensive development framework for creating secure, interoperable agents, a cloud-based platform for deployment, and an intelligent orchestration layer where an agent-native LLM translates high-level human goals into complex, multi-agent workflows. We demonstrate the deployed nature of this system through a decentralized logistics use case where autonomous agents dynamically discover, negotiate, and transact with one another securely. Ultimately, the Fetch.ai stack provides a principled architecture for moving beyond current agent implementations towards open, collaborative, and economically sustainable multi-agent ecosystems.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。