[最终作业] ST2516502 王春安 - 01 Agent - 记忆增强型文本交互智能体系统 - #53
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**实现方式：**基于 TextWorld 仿真环境、通义千问大模型（Qwen）与 FAISS 向量检索库，构建具备记忆与知识复用能力的大模型智能体。
**创新性：**本项目的核心创新在于将分层记忆机制、RAG 向量检索、自动规则提炼与 ReAct 智能体框架深度融合，有效解决了传统 ReAct 智能体无历史记忆、易重复执行失败动作、探索效率低等问题。
系统构建了记忆存储 — 向量检索 — 经验复用 — 规则提炼 — 决策优化的完整闭环，通过量化对比实验验证记忆模块对任务完成率、执行步数、决策有效性的提升效果，为面向多步决策任务的大模型智能体提供了可落地、可复现的经验复用方案。
项目独立代码仓库链接：
https://github.com/wca-159/Agent-WCA
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