Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

Simple Reinforcement learning tutorials

Minimal and Clean Reinforcement Learning Examples

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".

PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".

Deep Reinforcement Learning with pytorch & visdom

Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros

Scalable, event-driven, deep-learning-friendly backtesting library

Asynchronous Methods for Deep Reinforcement Learning

A3C LSTM Atari with Pytorch plus A3G design

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

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

Accompanying repository for Let's make a DQN / A3C series.

Simple A3C implementation with pytorch + multiprocessing

Deep Reinforcement Learning for the JVM (Deep-Q, A3C)

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

This is a simple implementation of DeepMind's PySC2 RL agents.

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

A continuous action space version of A3C LSTM in pytorch plus A3G design

Implementations of deep RL papers and random experimentation

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

A high-performance Atari A3C agent in 180 lines of PyTorch

Curiosity-driven Exploration by Self-supervised Prediction for Street Fighter III Third Strike

PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch

StarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

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

Combining deep learning and reinforcement learning.