# Agent Exchange: Shaping the Future of AI Agent Economics

arXiv: https://arxiv.org/abs/2507.03904 · HTML: https://mlsanity.com/paper/2507.03904/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use.
- Builds on 12 of its 31 references that are in the map.
- First posted on arXiv 5 Jul 2025.

## Placed in

- LLM agents and tool use / [General LLM agent frameworks and benchmarks](https://mlsanity.com/agents/general-llm-agent-frameworks-and-benchmarks/)

## Builds on (most cited first, 12 of 12)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023)
- [Small Language Models are the Future of Agentic AI](https://mlsanity.com/paper/2506.02153/) (2025)
- [EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms](https://mlsanity.com/paper/2406.14228/) (2024)
- [Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting](https://mlsanity.com/paper/1610.03013/) (2016)
- [Real-time Bidding for Online Advertising: Measurement and Analysis](https://mlsanity.com/paper/1306.6542/) (2013)
- [TRAD: Enhancing LLM Agents with Step-Wise Thought Retrieval and Aligned Decision](https://mlsanity.com/paper/2403.06221/) (2024)
- [Agents of Change: Self-Evolving LLM Agents for Strategic Planning](https://mlsanity.com/paper/2506.04651/) (2025)
- [RTBAgent: A LLM-based Agent System for Real-Time Bidding](https://mlsanity.com/paper/2502.00792/) (2025)
- [Understanding and Optimizing Agentic Workflows via Shapley value](https://mlsanity.com/paper/2502.00510/) (2025)
- [Using Multi-Agent Reinforcement Learning in Auction Simulations](https://mlsanity.com/paper/2004.02764/) (2020)

## Built on by (most cited first, 15 of 15)

- [Agentic Web: Weaving the Next Web with AI Agents](https://mlsanity.com/paper/2507.21206/) (2025)
- [Virtual Agent Economies](https://mlsanity.com/paper/2509.10147/) (2025)
- [Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets](https://mlsanity.com/paper/2510.25779/) (2025)
- [Intelligent AI Delegation](https://mlsanity.com/paper/2602.11865/) (2026)
- [BetaWeb: Towards a Blockchain-enabled Trustworthy Agentic Web](https://mlsanity.com/paper/2508.13787/) (2025)
- [Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web](https://mlsanity.com/paper/2604.02334/) (2026)
- [A Visualized Framework for Event Cooperation with Generative Agents](https://mlsanity.com/paper/2509.13011/) (2025)
- [Scaling Small Agents Through Strategy Auctions](https://mlsanity.com/paper/2602.02751/) (2026)
- [Shall We Play a Game? Language Models for Open-ended Wargames](https://mlsanity.com/paper/2509.17192/) (2025)
- [MALLES: A Multi-agent LLMs-based Economic Sandbox with Consumer Preference Alignment](https://mlsanity.com/paper/2603.17694/) (2026)
- [Blockchain Empowered Trustworthy Agent Networks: Foundations, Taxonomy, and Future Directions](https://mlsanity.com/paper/2608.04626/) (2026)
- [ToMPO: Training LLM Strategic Decision Making from a Multi-Agent Perspective](https://mlsanity.com/paper/2509.21134/) (2025)
- [When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets](https://mlsanity.com/paper/2512.04988/) (2025)
- [LEGIT: Credentialing Protocol for Trustworthy AI Agent Marketplaces](https://mlsanity.com/paper/2609.21325/) (2026)
- [TokenBank: Financial Infrastructure for AI Services](https://mlsanity.com/paper/2610.11333/) (2026)

## Abstract (arXiv)

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.