Simple Reinforcement learning tutorials

Repo for the Deep Reinforcement Learning Nanodegree program

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Modularized Implementation of Deep RL Algorithms in PyTorch

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

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

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

A PyTorch library for building deep reinforcement learning agents.

This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

PyTorch C++ Reinforcement Learning

RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code

RLgraph: Modular computation graphs for deep reinforcement learning

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

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

RAD: Reinforcement Learning with Augmented Data

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

Lightweight, stable, efficient PyTorch implement of reinforcement learning. I want to call this PyTorch implement as "3-Python-file-RL".

Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020.

ROS 2 enabled Machine Learning algorithms

Reinforcement learning models in ViZDoom environment

A pytorch tutorial for DRL(Deep Reinforcement Learning)

Trading Environment(OpenAI Gym) + PPO(TensorForce)