https://github.com/cedrickchee/rl-algorithms
A collection of Reinforcement Learning algorithms.
https://github.com/cedrickchee/rl-algorithms
deep-learning deep-reinforcement-learning jupyter-notebooks neural-networks openai-gym-agents reinforcement-learning reinforcement-learning-excercises
Last synced: 2 months ago
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A collection of Reinforcement Learning algorithms.
- Host: GitHub
- URL: https://github.com/cedrickchee/rl-algorithms
- Owner: cedrickchee
- License: mit
- Created: 2018-08-09T16:30:12.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-08-10T17:03:15.000Z (almost 7 years ago)
- Last Synced: 2025-01-18T17:49:34.959Z (4 months ago)
- Topics: deep-learning, deep-reinforcement-learning, jupyter-notebooks, neural-networks, openai-gym-agents, reinforcement-learning, reinforcement-learning-excercises
- Language: Jupyter Notebook
- Size: 1.46 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Introduction
This repository contains my notebook and code for practices and implementations for common Reinforcement Learning (RL) algorithms. These are meant to serve as an educational materials.
Each directory is corresponds to one or more RL algorithms.
All code is written in Python 3 and uses RL environments from [OpenAI Gym](https://gym.openai.com/). Advanced techniques use TensorFlow for neural network implementations.
# Table of Contents
- Introduction to RL
- Q-Learning
- Deep Q-Learning (DQN)
- Beyond DQN: Dueling DQN, Double DQN
- Policy Gradient
- Advantage Actor Critic (A2C)
- Asynchronous Advantage Actor Critic (A3C)
- Proximal Policy Optimization (PPO)
# List of Implemented Algorithms
- Q-Learning with OpenAI Gym Taxi-v2