[R] Autonomous Mathematical Discovery in an Open-World Multi-Agent Environment
在一个开放世界的多智能体环境中，Station 在 12 个 AlphaEvolve 构建问题和两个案例研究中实现了自主数学发现。新颖的成果包括有限域 Kakeya 集的新无限族、维度 11 中精确的 604 点接吻构型、离散 Kakeya 针和符号不确定性问题的新记录，以及 Erdős 最小重叠问题的改进下限。智能体还发现了 Book Ramsey 数的新无限族，并生成了数值构造、定理和分析来解释其工作原理。
We study autonomous mathematical discovery in the Station, an open-world multi-agent environment in which AI agents from different model families pursue a shared research goal without a central coordinator or scripted pipeline. Agents choose their own research directions, conduct experiments, collaborate, and build a shared scientific literature.
Across 12 construction problems from the AlphaEvolve catalogue and two additional case studies, the Station obtained results novel relative to the prior literature on five problems: a new infinite family of finite-field Kakeya sets, new exact 604-point kissing configurations in dimension 11, new records for the discretized Kakeya needle and sign uncertainty problems, and a substantially improved lower bound for Erdős's minimum-overlap problem.
Agents also discovered novel infinite families for Book Ramsey numbers. Importantly, the agents produced not only numerical constructions but also theorems and analyses explaining how those constructions work, making the results more interpretable and easier for mathematicians to build upon. We release all raw agent dialogues, proofs, and verification code, providing a transparent record of how these discoveries emerged.