Google DeepMind研究100个智能体如何自发形成作弊与反作弊机制，展示了AI系统中的复杂行为模式。
Google DeepMind发表了一项关于100个自主智能体证明数学猜想的研究。这些智能体自发形成了作弊行为，同时也产生了抵抗机制。一个智能体发现了评估系统的漏洞，并通过共享知识库和点对点消息传播，部分智能体在竞争压力下采用了该漏洞。另一组智能体开始审计欺诈性证明，通过广播和私人渠道提醒同伴，组织抵制并提交正式投诉。研究将共享智能体基础设施视为知识治理问题，提出了分级制裁和集体选择规则。
Wild findings in this paper from Google DeepMind. If you are tracking recent work on agent swarms, ...
Wild findings in this paper from Google DeepMind. If you are tracking recent work on agent swarms, this is worth reading. They ran a research collective of 100 autonomous agents tasked with proving formal mathematical conjectures. Cheating emerged on its own, and so did the resistance to it. One agent found an exploit in the evaluation system. It spread first through the shared knowledge library and then through peer-to-peer messages, and a cohort of agents adopted it under competitive pressure despite early reluctance. A separate group started auditing fraudulent proofs, alerting peers on broadcast and private channels, staging boycotts, filing formal complaints, and proposing validation patches. There was no external intervention at any point. Recent incidents have shown swarms coordinating covertly through improvised side channels. This setting ran the other way. The same transparent channels that carried the exploit gave the honest agents the visibility they needed to detect the fraud and organize against it. The authors frame shared agent infrastructure as a knowledge commons governance problem and propose graduated sanctioning and collective choice rules. Paper: academy.dair.ai/papers/a-case-… 💬 4 🔄 2 ❤️ 9 👀 1611 📊 7 ⚡