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

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

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)

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

PyTorch C++ Reinforcement Learning

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

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

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

Code accompanying the blog post "Deep Reinforcement Learning with TensorFlow 2.1"

A Clearer and Simpler Synchronous Advantage Actor Critic (A2C) Implementation in TensorFlow

A library for ready-made reinforcement learning agents and reusable components for neat prototyping

StarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)

A pytorch tutorial for DRL(Deep Reinforcement Learning)

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

Implementing reinforcement-learning algorithms for pysc2 -environment

Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]

This is the pytorch implementation of ICML 2018 paper - Self-Imitation Learning.

25 projects in the framework of Deep Reinforcement Learning algorithms: DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

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

Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO