hztBUAA/RL-learning

learn from MOFAN.

Reinforcement Learning Methods and Tutorials

In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.

If you speak Chinese, visit 莫烦 Python or my Youtube channel for more.

As many requests about making these tutorials available in English, please find them in this playlist: (https://www.youtube.com/playlist?list=PLXO45tsB95cIplu-fLMpUEEZTwrDNh6Ba)

Table of Contents

• Tutorials
  • Simple entry example
  • Q-learning
  • Sarsa
  • Sarsa(lambda)
  • Deep Q Network (DQN)
  • Using OpenAI Gym
  • Double DQN
  • DQN with Prioitized Experience Replay
  • Dueling DQN
  • Policy Gradients
  • Actor-Critic
  • Deep Deterministic Policy Gradient (DDPG)
  • A3C
  • Dyna-Q
  • Proximal Policy Optimization (PPO)
  • Curiosity Model, Random Network Distillation (RND)
• Some of my experiments
  • 2D Car
  • Robot arm
  • BipedalWalker
  • LunarLander

Some RL Networks

Deep Q Network

Double DQN

Dueling DQN

Actor Critic

Deep Deterministic Policy Gradient

A3C

Proximal Policy Optimization (PPO)

Curiosity Model

Donation

If this does help you, please consider donating to support me for better tutorials. Any contribution is greatly appreciated!