Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

Evolution Gym A large-scale benchmark for co-optimizing the design and control of soft robots. As seen in Evolution Gym: A Large-Scale Benchmark for E

Automating reinforcement learning architecture design for code optimization. Che

Rainbow Rainbow: Combining Improvements in Deep Reinforcement Learning [1]. Results and pretrained models can be found in the releases. DQN [2] Double

The Malmo Collaborative AI Challenge - Team Pig Catcher Approach The challenge involves 2 agents who can either cooperate or defect. The optimal polic

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay This is the official implementation of our paper "Diversity-based Traje

This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available

FinRL-Meta: A Universe of Market Environments. FinRL-Meta is a universe of market environments for data-driven financial reinforcement learning. Users

GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic

PPO-based Autonomous Navigation for Quadcopters This repository contains an implementation of Proximal Policy Optimization (PPO) for autonomous naviga

Description DeepRTS is a high-performance Real-TIme strategy game for Reinforcement Learning research. It is written in C++ for performance, but provi

Deep Reinforcement Learning in TensorFlow TensorFlow implementation of Deep Reinforcement Learning papers. This implementation contains: [1] Playing A

A rough implementation of the paper "A Steering Algorithm for Redirected Walking Using Reinforcement Learning"

AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning AutoPentest-DRL is an automated penetration testing framework based o

NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C

Deep Reinforcement Learning for Smart Cities Documentation RLlib: https://docs.ray.io/en/master/rllib.html Mesa: https://mesa.readthedocs.io/en/stable

Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose

Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi

The Hands-on Reinforcement Learning course 🚀 From zero to HERO 🦸🏻‍🦸🏽 Out of intense complexities, intense simplicities emerge. -- Winston Churchi

Trax — Deep Learning with Clear Code and Speed Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively us

Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup

pytorch-a2c-ppo-acktr Update (April 12th, 2021) PPO is great, but Soft Actor Critic can be better for many continuous control tasks. Please check out

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

PyTorch implementation of TRPO Try my implementation of PPO (aka newer better variant of TRPO), unless you need to you TRPO for some specific reasons.

spatial-action-maps Update: Please see our new spatial-intention-maps repository, which extends this work to multi-agent settings. It contains many ne

spatial-intention-maps This code release accompanies the following paper: Spatial Intention Maps for Multi-Agent Mobile Manipulation Jimmy Wu, Xingyua

Deep Reinforcement Learning with pytorch & visdom Sample testings of trained agents (DQN on Breakout, A3C on Pong, DoubleDQN on CartPole, continuous A

SLM Lab Modular Deep Reinforcement Learning framework in PyTorch. Documentation: https://slm-lab.gitbook.io/slm-lab/ BeamRider Breakout KungFuMaster M

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.

Decentralized Reinforcement Learning This is the code complementing the paper Decentralized Reinforcment Learning: Global Decision-Making via Local Ec

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

Learning to Communicate with Deep Multi-Agent Reinforcement Learning This is a PyTorch implementation of the original Lua code release. Overview This

neptune-contrib Documentation See neptune-contrib documentation site Installation Get prerequisites python versions 3.5.6/3.6 are supported Install li

Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur

Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea

Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This

Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is

Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,

Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,

DRL-robot-navigation Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gra

Deep Trading Agent Deep Reinforcement Learning based Trading Agent for Bitcoin using DeepSense Network for Q function approximation. For complete deta

Bayesian Deep Learning for Manufacturing 2.0 (dlmfg) Object Shape Error Response (OSER) Digital Lifecycle Management - In Process Quality Improvement

d3rlpy: An offline deep reinforcement learning library d3rlpy is an offline deep reinforcement learning library for practitioners and researchers. imp

MINERVA is an out-of-the-box GUI tool for offline deep reinforcement learning, designed for everyone including non-programmers to do reinforcement learning as a tool.

pytoch-dqn This project is pytorch implementation of Human-level control through deep reinforcement learning and I also plan to implement the followin

Recurrent Model-Free RL is a Strong Baseline for Many POMDPs Welcome to the POMDP world! This repo provides some simple baselines for POMDPs, specific

CleanRL (Clean Implementation of RL Algorithms) CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation

V-MPO Simple code to demonstrate Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO) in Pyt

Using Deep Q-Network to Learn How To Play Flappy Bird 7 mins version: DQN for flappy bird Overview This project follows the description of the Deep Q