Initial commit: Add reinforcement learning study materials and grid world code

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# Python
__pycache__/
*.py[cod]
*$py.class
# Jupyter Notebook
.ipynb_checkpoints
*/.ipynb_checkpoints/*
# Distribution / Packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
# Virtual Environments
venv/
env/
.env
.venv/
ENV/
env.bak/
venv.bak/
# IDEs
.vscode/
.idea/
# OS specific files
.DS_Store
Thumbs.db
# Byte-compiled / optimized / DLL files
*.pyc
*.pyd
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My lecture slides are put into two folders.
- The folder "slidesForMyLectureVideos" contains all **the slides that I used to record my lecture videos**.
- The folder "slidesContinuouslyUpdated" contains **the slides that I updated continuously**.
The slides in the two folders are very similar, but there are some minor differences, such as typo correction and content adjustment.
**If you are not studying my online lecture videos, I suggest you check the slides in the slidesContinuouslyUpdated folder since they have been improved continuously.**
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# RL-Study # 强化学习的数学基础
用于学习RL的相关知识,参考书目《强化学习的数学方法》 本项目是我在学习赵世钰老师书籍 **《Mathematical Foundations of Reinforcement Learning》** 时建立的个人仓库。主要用于记录学习笔记、公式推导,以及使用 Python/Jupyter Notebook 复现书中的算法和 Grid World 示例。
## 📚 关于原书 (Original Book)
本项目的核心内容基于赵世钰老师的开源书籍,以下是原书的相关信息:
- **书名**: Mathematical Foundations of Reinforcement Learning
- **作者**: Shiyu Zhao (Westlake University)
- **GitHub 仓库**: [Book-Mathematical-Foundation-of-Reinforcement-Learning](https://github.com/MathFoundationRL/Book-Mathematical-Foundation-of-Reinforcement-Learning)
- **配套视频**:
- [Bilibili (中文)](https://space.bilibili.com/2044042934)
- [YouTube (English)](https://youtube.com/playlist?list=PLEhdbSEZZbDaFWPX4gehhwB9vJZJ1DNm8)
---
## 📂 项目结构
本项目主要包含以下内容:
- `Code for grid world/`:
- `python_version/`: 使用 Python 复现的 Grid World 环境及相关算法。
- `matlab_version/`: (可选) 原书提供的 Matlab 参考代码。
- `Lecture slides/`: 课程相关的幻灯片或我的注解。
- `Notebooks/`: (计划中) 包含详细推导和实验过程的 Jupyter Notebooks。
## 🛠️ 环境配置
本项目使用 Python 进行开发。推荐使用 `uv``conda` 管理环境。
```bash
# 安装依赖 (示例)
pip install numpy matplotlib jupyter
```
## 📝 开源协议 (License)
### 关于代码
本项目中由本人编写的复现代码遵循 **MIT License** 开源协议。这意味着你可以自由地使用、修改和分发这些代码,但请保留原作者的版权声明。
### 关于笔记
项目中的学习笔记内容仅供个人学习交流使用。
---
## 🤝 致谢
特别感谢赵世钰老师提供的精彩教材和开源资源,帮助我们深入理解强化学习的数学原理。
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