---
id: 20260905-T0-16
title: "LLM智能体团队协作出错：新鲜记忆却按过时计划执行"
title_en: "Distributed LLM Agents Act on Stale Plans Despite Fresh Memory"
url: https://ai.daily.yangsir.net/daily/20260905-T0-16
issue_date: 2026-09-05
publish_date: 2026-09-04T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2609.03340
---

# LLM智能体团队协作出错：新鲜记忆却按过时计划执行

新论文指出，分布式LLM智能体团队即使读取最新共享事实，仍可能执行过时计划。例如规划者基于需求r3制定行动，其他成员提交r4，执行者收到r4后却未更新旧计划。论文提出依赖范围验证方法，确保行动与最新需求一致。

## English Version

**Distributed LLM Agents Act on Stale Plans Despite Fresh Memory**

A new paper reveals distributed LLM-agent teams can read current facts yet act on stale plans. When a planner acts on r3 and another commits r4, the executor may not replace the old plan. Dependency-scoped validation ensures actions align with latest requirements.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2609.03340)

**详情页**：https://ai.daily.yangsir.net/daily/20260905-T0-16

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