arXiv 论文提出"研究者社会"框架：让上万个自主研究智能体共享算力协作
A Society of Researchers: Designing Institutions for Populations of Autonomous Research Agents
这篇论文讨论怎么管上万个抢算力的研究智能体，用招标加拨款代替人工派活，还跑了万人规模实验，做 agent 系统的可以看看。
arXiv 论文 2610.10468 针对研究智能体从单个项目扩展到上千个共享算力池的现状，提出"智能体社会"设计思路。作者主张设计者应显式提供组织制度，而不是任由群体自发形成组织。具体方案是"研究者社会"：首席 investigator 通过研究招标、独立评审和拨款机制竞争算力，一个名为 mayor 的人类治理者只分配资源不指派任务。在一个运行中的万人研究者社会里，任务被设定为改进语言模型预训练，其中一个实验室报告了节省约 30% 算力达到同等质量的方法，但测试该方法的实验室之间尚未达成一致结论。
A Society of Researchers: Designing Institutions for Populations of Autonomous Research Agents
Deployments of research agents are moving to populations of thousands that share one pool of compute, while most current systems organize one project at a time or leave the population unorganized. We argue that such a population will acquire an organization whether or not its designers provide one, so designers should provide it explicitly, and that the multi-agent systems community holds the tools to do so. We propose a society of agents, a population of persistent agents under explicit institutions, and develop it for science as a society of researchers built on six principles. Principal investigators compete for compute through requests for proposals, independent review, and grants; a human governor, the mayor, allocates resources and assigns no tasks. In a running society of ten thousand researchers, asked only to improve the pretraining of language models, one lab reported a way to reach the same quality with about 30% less compute, a result the labs that tested it do not yet agree on. We close with six open problems for the agents community.
