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Rohan Paul· @rohanpaul_ai · X· · 原发布时间 AI 评分54

斯坦福新论文:多人各用一个 AI 智能体管理共享资源,效果不及统一协调

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一项斯坦福新论文称,在五个前沿模型的测试中,由一个智能体统筹所有人的需求,比每人各用一个智能体处理共享预算或日历效果更好。各智能体单独看能完成本人的任务,但协作时会互相覆盖;在一项争夺令牌预算的测试中,Opus 5 多智能体团队取得可实现价值的30%,统一协调的智能体取得64%。

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New Stanford paper finds that when each person's agent acts alone on a shared resource, the group does worse than 1 agent serving everyone.

A shared budget or calendar is handled better by 1 agent serving everyone than by 1 agent per user, across 5 frontier models.

Each agent does a sensible job for its own user.

Together they overwrite each other, stall as the team grows, and with no channel they collapsed outright in 2 environments.

On a contested token budget, Opus 5 teams captured 30% of the achievable value against 64% for 1 coordinating agent. Agents invented facts about other users in more than half of Claude team episodes in the group-ordering environment.

Prefer 1 agent holding everyone's constraints, and if you run 1 per user, make reading peers a condition of committing.

来源:Rohan Paul · x.com

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