Title: Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets
Primary area: datasets and benchmarks
Keywords: agents, LLMs, communication, delegation, asymmetric information

Abstract: As LLM agents advance, they increasingly act as intermediaries for humans in economic decisions, ranging from product discovery to transactions. While this automation promises benefits, it also raises responsibility as agents begin to make consequential choices on behalf of users.
Previous research has largely focused on evaluating agent performance in constrained settings, such as single-task marketplaces (e.g., negotiation) or structured two-agent interactions. In contrast, real-world markets introduce far greater complexity which requires agents to handle diverse economic activities and coordinate within large, dynamic ecosystems where multiple agents with opaque behaviors engage in open-ended dialogues.
These stakes and complexity motivate empirical testing of agent behavior in markets before real-world deployment.
We investigate {\em two-sided agentic marketplaces} where Assistant agents represent consumers and Service agents represent competing businesses,and develop a simulated environment---Magentic Marketplace---where Assistants and Services can safely operate. 
This enables understanding, \emph{e.g.}, the utility agents can achieve, any behavioral biases, vulnerability to manipulation, or even how search/discovery mechanisms shape market outcomes.
Our simulated experiments in Magentic Marketplace show that some frontier models improve market welfare outcomes over non-agentic baselines, but performance degrades as business scale increases. We also find that even the best-performing models remain vulnerable to market manipulation tactics and behavioral biases. These findings reveal how behaviors emerge across market conditions, informing the design of fair and efficient agentic marketplaces. Source code: \url{https://anonymous.4open.science/r/Magentic-Marketplace}

TL;DR: The Magentic-Marketplace provides a controlled environment to study complex two-sided marketplaces where AI agents discover each other and communicate to transact and negotiate good and services.