强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

An elegant PyTorch deep reinforcement learning library.

Modularized Implementation of Deep RL Algorithms in PyTorch

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

User can set up destination for any agent to navigate on Google Map and learn the best route for the agent based on its current condition and the traffic. Our result is 10% less energy consumption than the route provided by Google map

Repository for codes of 'Deep Reinforcement Learning'

Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.

An RL model that uses double deep Q learning to generate an optimal policy of stock market trades

Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO

Pytorch implementation of distributed deep reinforcement learning

An implementation of (Double/Dueling) Deep-Q Learning to play Super Mario Bros.

Solving board games like Connect4 using Deep Reinforcement Learning

This is an implementation of Deep Q Learning (DQN) playing Breakout from OpenAI's gym with Keras.

A Reinforcement Learning agent to perform overtaking action using Double DQN based CNNs which takes images as input built using TensorFlow.

Deep Reinforcement Learning for Trading