构建AI代理经济的拍卖平台，让智能体自主交易与协作。
Agent Exchange: Shaping the Future of AI Agent Economics
- 设计AEX拍卖系统，支持代理间价值交换与协调
- 四类组件协同运作，实现从任务到执行的闭环
- 适合研究智能体经济、市场机制的学者与开发者
大语言模型的兴起使AI代理从被动计算工具演变为自主经济主体，推动了以代理为中心的经济形态出现。为此，我们提出Agent Exchange（AEX），一个专为AI代理市场设计的拍卖平台，支撑代理间的动态交互。AEX借鉴在线广告中的实时竞价（RTB）机制，作为核心拍卖引擎，连接四大组件：用户侧平台（USP）将人类目标转化为可执行任务；代理侧平台（ASP）负责能力表征、性能追踪与优化；代理枢纽（Agent Hubs）协调代理团队并参与拍卖；数据管理平台（DMP）保障知识共享安全与价值公平分配。本文阐述AEX的设计原则与系统架构，为未来基于代理的经济基础设施奠定基础。
原文摘要 · Abstract (English)
The rise of Large Language Models (LLMs) has transformed AI agents from passive computational tools into autonomous economic actors. This shift marks the emergence of the agent-centric economy, in which agents take on active economic roles-exchanging value, making strategic decisions, and coordinating actions with minimal human oversight. To realize this vision, we propose Agent Exchange (AEX), a specialized auction platform designed to support the dynamics of the AI agent marketplace. AEX offers an optimized infrastructure for agent coordination and economic participation. Inspired by Real-Time Bidding (RTB) systems in online advertising, AEX serves as the central auction engine, facilitating interactions among four ecosystem components: the User-Side Platform (USP), which translates human goals into agent-executable tasks; the Agent-Side Platform (ASP), responsible for capability representation, performance tracking, and optimization; Agent Hubs, which coordinate agent teams and participate in AEX-hosted auctions; and the Data Management Platform (DMP), ensuring secure knowledge sharing and fair value attribution. We outline the design principles and system architecture of AEX, laying the groundwork for agent-based economic infrastructure in future AI ecosystems.
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