---
id: 20260430-T0-09
title: "从粗粒度到细粒度：LLM智能体自适应分层规划"
title_en: "Self-Adaptive Hierarchical Planning for LLM Agents"
url: https://ai.daily.yangsir.net/daily/20260430-T0-09
issue_date: 2026-04-30
publish_date: 2026-04-29T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2604.23194
---

# 从粗粒度到细粒度：LLM智能体自适应分层规划

研究人员提出新型分层规划框架，通过自适应机制提升LLM智能体在动态环境中的多步任务执行能力。该方法解决了传统静态规划的局限性，在复杂场景中表现更优。

## English Version

**Self-Adaptive Hierarchical Planning for LLM Agents**

Researchers introduced a hierarchical planning framework with adaptive mechanisms, improving LLM agents' multi-step task execution in dynamic environments. This addresses limitations of traditional static planning.

---

**来源**：[arXiv cs.AI](https://arxiv.org/abs/2604.23194)

**详情页**：https://ai.daily.yangsir.net/daily/20260430-T0-09

---

*智语观潮 · Daily — https://ai.daily.yangsir.net/llms.txt*