这篇论文用DeepSeek-V3模拟了18个AI代理的市场，发现加入调解机制能抗住攻击，效用只降13%但市场不会崩盘。
本研究通过多智能体市场模拟，实验了18个使用DeepSeek-V3模型的LLM代理在约束社交网络中交易的情景。在200轮实验中比较了8种机制，发现Mediation机制表现最佳。通过迭代优化提示的LLM驱动攻击进行对抗性测试，最强攻击（v6）仅使诚实代理效用降低13.3%，无法导致市场崩溃。研究证实Mediation机制在持续对抗压力下仍能维持市场稳定。
Formal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation Study
Self-interested agents, left unconstrained, tend toward defection in repeated social dilemmas, causing cooperative gains from trade to collapse. This paper investigates what formal mechanisms, layered on top of unrestricted communication, are sufficient for a society of such agents to maintain market stability, and how resilient those mechanisms are to adversarial attack. We instantiate the research question as a multi-agent marketplace simulation where 18 LLM agents (DeepSeek-V3) with complementary production specialties must trade within a constrained social network to obtain utility. We conduct two experimental phases: (1) a mechanism comparison across eight conditions under progressive troll injection over 200 rounds, identifying Mediation as the top-performing mechanism; and (2) adversarial red-teaming of Mediation using iteratively prompt-optimised LLM-driven trolls, finding that the best attack (v6) reduces honest-agent utility by 13.3% but cannot collapse the market. Mediation enables recovery even under sustained adversarial pressure. We define adversarial robustness as a mechanism's ability to sustain positive honest-agent utility under optimised attack, and find that Mediation is robust: it can be bent but not broken.