# 本章小结

本章深入探讨了智能体“大脑”的核心能力，但重点不应理解为一条从 CoT 到 Prompt Engineering 的单线链条，而应理解为一组可组合的方法层：CoT 负责展开局部推理，ToT/GoT 负责搜索与规划，ReAct 负责把推理接到行动闭环上，Reflexion 负责在反馈中修正策略，而提示词工程负责把角色、约束、工具与上下文组织成稳定可控的运行接口。

## 关键概念清单

* **思维链 (CoT)**：把复杂问题拆成连续步骤，适合局部推理展开
* **任务分解 (ToT/GoT)**：用树或图的搜索结构组织候选路径与子任务
* **ReAct**：把推理与工具调用连接成可执行闭环
* **Reflexion**：在失败、评估与反馈中修正后续策略
* **提示词工程**：以角色、约束、工具、示例和上下文编排整个能力栈

## 下一步

有了强大的推理引擎后，智能体还需要海量知识储备。下一章进入记忆系统构建，探讨如何打破上下文限制、实现长期记忆。

***

**下一章**: [第三章：记忆系统与上下文工程](/agentic_ai_guide/di-yi-bu-fen-dan-ti-zhi-neng-jia-gou/03_memory.md)


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