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drl-algorithms

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trials

Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the proposed method and experimental results on real-world stock data to demonstrate its effectiveness.

  • Updated Aug 31, 2023
  • Python

本项目是作者(MRL Liu)使用AI算法的强化学习方法玩迷宫游戏的一个阶段性总结,本项目的迷宫游戏是简单的方格迷宫,其状态空间和动作空间都足够简单,是作者整理的手中的第1个RL项目。该项目重构了作者之前学习时的一些基于Value的RL算法,将它们的例如经验回放池的对象等抽象出来为一个对象,便于整理知识网络。该项目的原始算法代码使用的是莫烦Python的相关实现,在此向莫烦老师表示感谢。本项目的特色是使用了统一范式的代码来定义基于Value的算法系列的实现,封装了Q-Table和ReplayBuffer对象;添加了网络模型的保存与加载功能、TensorFlow可视化功能、经验池保存和加载等。整个项目基于良好的面向对象思想,方法定义层层推进。

  • Updated May 2, 2021
  • Python

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