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README.md

《PARL强化学习入门实践》课程示例

针对强化学习初学者，PARL提供了入门课程，展示最基础的5个强化学习算法代码示例。

课程大纲

  • 一、强化学习(RL)初印象
    • RL概述、入门路线
    • 实践：环境搭建（lesson1 的代码提供了格子环境世界的渲染封装）
  • 二、基于表格型方法求解RL
  • 三、基于神经网络方法求解RL
    • 函数逼近方法
    • 实践：DQN
  • 四、基于策略梯度求解RL
  • 五、连续动作空间上求解RL

使用说明

安装依赖（注意：请务必安装对应的版本）

运行示例

进入每个示例对应的代码文件夹中，运行

python train.py
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PARL 是一个高性能、灵活的强化学习框架

Python C++ JavaScript Markdown Shell other

Please read the following content carefully:

Dear OpenI User

Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.

For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》

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