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DAIR.AI· @dair_ai · X·· 3 小时前AI 评分53
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哈佛-MIT 论文(arXiv:2609.36365)在拍卖和匹配市场等有已知最优策略的环境中测试 LLM Agent,发现让 Agent 提前规划或考虑对手的提示词总体上使决策变差。改用每次呈现一个安全选择的升价拍卖界面,在四个模型族中降低了出价错误;说明收益和真实出价为何安全的描述也有帮助。Agent 的口头计划与实际选择并不一致,作者建议按脚手架产生的实际决策来评估。

正文

Does telling your agent to plan ahead actually help?

It's standard practice to add a "plan ahead" or "think about the other players" instruction to an agent's prompt.

In auctions and matching markets, this Harvard-MIT paper finds that those prompts make play worse overall.

The authors use settings with known optimal strategies, so they can score every choice.

What helped was changing the interface.

An ascending auction, which presents one safe choice at a time, reduced bid errors across four model families. Plain descriptions of the payoffs and of why truthful bidding is safe also helped.

The agents' stated plans did not track their choices.

Interventions that improved bids left the measured reasoning quality in the plans unchanged, and some prompts improved the plans without improving bids.

The takeaway here is to evaluate a scaffold on the decisions it produces.

Paper: https://arxiv.org/abs/2609.36365

Chat with Paper: https://academy.dair.ai/papers/engineering-simplicity-simple-mechanism-interfaces-steer-llm-agents-2609.36365

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