学习资料总结

• 书

  • Reinforcement Learning: An Introduction
  • Multi-agent Machine Learning: A Reinforcement Approach

• 课程

  • 基础课程
    • David Silver 强化学习课程
  • MARL课程
    • Multi-Agent Reinforcement Learning Tutorial
  • DRL课程
    • 台湾大学 李宏毅 （深度）强化学习

• 代码

• 论文

  • NIPS

书

Reinforcement Learning: An Introduction

Github转存PDF: link

Multi-agent Machine Learning: A Reinforcement Approach

Github转存PDF: link

课程

基础课程

David Silver 强化学习课程（UCL2015）

Github转存 link

课程主页：link

Lecture 1: Introduction to Reinforcement Learning link

Lecture 2: Markov Decision Processes link

Lecture 3: Planning by Dynamic Programming link

Lecture 4: Model-Free Prediction link

Lecture 5: Model-Free Control link

Lecture 6: Value Function Approximation link

Lecture 7: Policy Gradient Methods link

Lecture 8: Integrating Learning and Planning link

Lecture 9: Exploration and Exploitation link

Lecture 10: Case Study: RL in Classic Games link

MARL课程

Multi-Agent Reinforcement Learning Tutorial（SJTU2018）

Github转存 link

课程主页 link

Lecture1: Fundamentals of Reinforcement Learning link

Lecture2a: Fundamentals of Game Theory link

Lecture2b: Learning in Repeated Games link

Lecture3a: Multi-Agent Reinforcement Learning(a) link

Lecture3b: Multi-Agent Reinforcement Learning(b) link

DRL课程

台湾大学 李宏毅 （深度）强化学习

课程主页 link

视频可以在B站上看到：link

代码

结合他人的代码对RL的练习：link

论文

NIPS

2018 link