# introRL

**Repository Path**: phyzy/introRL

## Basic Information

- **Project Name**: introRL
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-03-25
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Intro to Reinforcement Learning (强化学习纲要）
![teaser](asset/teaser.png)
## Overview
This short course will introduce basic concepts of reinforcement learning in a nutshell. Slides will be made in English and lectures will be given by [Bolei](http://bzhou.ie.cuhk.edu.hk/) in Chinese. The course is for entertainment only.  

## Course Schedule
The short course will be arranged as follows. Lectures 1-8 will be the foundation, the others will be the advanced topics, which are optional.

|            	| Topic                                      	| Resources 	|
|------------	|--------------------------------------------	|-----------	|
|  Lecture 1 	| Overview                                   	|[slide](lecture1.pdf), [youtube1](https://www.youtube.com/watch?v=IkEF4LpH5Ys), [youtube2](https://www.youtube.com/watch?v=Qu8CPnnwplM), [B站1](https://www.bilibili.com/video/av96436833/), [B站2](https://www.bilibili.com/video/av96834288/)  |
|  Lecture 2 	| Markov Decision Process                    	| [slide](lecture2.pdf), [youtube1](https://www.youtube.com/watch?v=6yE9XiIB3hQ), [youtube2](https://www.youtube.com/watch?v=MIZbocCu7Sk), [B站1](https://www.bilibili.com/video/av98583371/), [B站2](https://www.bilibili.com/video/av98583913/) |
|  Lecture 3 	| Model-free Prediction and Control          	|           	|
|  Lecture 4 	| On-policy and Off-policy Learning          	|           	|
|  Lecture 5 	| Value Function Approximation               	|           	|
|  Lecture 6 	| Policy Optimization: Basics                	|           	|
|  Lecture 7 	| Policy Optimization: State of the art      	|           	|
|  Lecture 8 	| Model-based RL                             	|           	|
|  Lecture 9 	| Imitation Learning                         	|           	|
| Lecture 10 	| Distributed computing and RL system design 	|           	|
| Lecture 11 	| Case Study on AlphaGo Series               	|           	|
| Lecture 12 	| Case Study on AlphaStar and OpenAI Five    	|           	|
| Lecture 13 	| Unsupervised Learning                      	|           	|
| Lecture 14 	| Generative Modeling                        	|           	|
| TBD        	| ...                                        	|           	|