bargaining

This paper studies how LLM agents negotiate in a dynamic supply chain bargaining problem, benchmarking nine models from OpenAI, Google, and Alibaba against a Bayesian equilibrium and finding that capability, provider identity, and prompt design shape surplus creation and division.

IAB@NeurIPS 2026 竞赛（GLEE Competition）公告，参赛者需构建能在实时多轮博弈中进行讨价还价、谈判与说服的 AI 智能体，总奖金池 6,000 美元，并可选择性提交论文。

研究表明，LLM智能体在谈判中能够建模对手的偏好，但未能将这种知识转化为战略性讨价还价以改善结果，这限制了它们在多轮谈判中的有效性。