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A curated list of awesome Deep Reinforcement Learning resources.

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Awesome Deep RL Awesome

A curated list of awesome Deep Reinforcement Learning resources.



  • Berkeley Ray RLLib - An open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications.
  • Berkeley Softlearning - A reinforcement learning framework for training maximum entropy policies in continuous domains.
  • Catalyst - Accelerated DL & RL.
  • ChainerRL - A deep reinforcement learning library built on top of Chainer.
  • DeepMind Acme - A research framework for reinforcement learning.
  • DeepMind OpenSpiel - A collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
  • DeepMind TRFL - TensorFlow Reinforcement Learning.
  • DeepRL - Modularized Implementation of Deep RL Algorithms in PyTorch.
  • DeepX machina - A library for real-world Deep Reinforcement Learning which is built on top of PyTorch.
  • Facebook ELF - A platform for game research with AlphaGoZero/AlphaZero reimplementation.
  • Facebook ReAgent - A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)
  • garage - A toolkit for reproducible reinforcement learning research.
  • Google Dopamine - A research framework for fast prototyping of reinforcement learning algorithms.
  • Google TF-Agents - TF-Agents is a library for Reinforcement Learning in TensorFlow.
  • MAgent - A Platform for Many-agent Reinforcement Learning.
  • Maze - Application-oriented deep reinforcement learning framework addressing real-world decision problems.
  • MushroomRL - Python library for Reinforcement Learning experiments.
  • NervanaSystems coach - Reinforcement Learning Coach by Intel AI Lab.
  • OpenAI Baselines - High-quality implementations of reinforcement learning algorithms.
  • pytorch-a2c-ppo-acktr-gail - 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).
  • pytorch-rl - Model-free deep reinforcement learning algorithms implemented in Pytorch.
  • reaver - A modular deep reinforcement learning framework with a focus on various StarCraft II based tasks.
  • RLgraph - Modular computation graphs for deep reinforcement learning.
  • RLkit - Reinforcement learning framework and algorithms implemented in PyTorch.
  • rlpyt - Reinforcement Learning in PyTorch.
  • SLM Lab - Modular Deep Reinforcement Learning framework in PyTorch.
  • Stable Baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms.
  • TensorForce - A TensorFlow library for applied reinforcement learning.
  • Tianshou - Tianshou (天授) is a reinforcement learning platform based on pure PyTorch.
  • UMass Amherst Autonomous Learning Library - A PyTorch library for building deep reinforcement learning agents.
  • Unity ML-Agents Toolkit - Unity Machine Learning Agents Toolkit.
  • vel - Bring velocity to deep-learning research.

Benchmark Results


  • AI2-THOR - A near photo-realistic interactable framework for AI agents.
  • Animal-AI Olympics - An AI competition with tests inspired by animal cognition.
  • Berkeley rl-generalization - Modifiable OpenAI Gym environments for studying generalization in RL.
  • BTGym - Scalable event-driven RL-friendly backtesting library. Build on top of Backtrader with OpenAI Gym environment API.
  • Carla - Open-source simulator for autonomous driving research.
  • CuLE - A CUDA port of the Atari Learning Environment (ALE).
  • Deepdrive - End-to-end simulation for self-driving cars.
  • DeepMind AndroidEnv - A library for doing RL research on Android devices.
  • DeepMind DM Control - The DeepMind Control Suite and Package.
  • DeepMind Lab - A customisable 3D platform for agent-based AI research.
  • DeepMind pycolab - A highly-customisable gridworld game engine with some batteries included.
  • DeepMind PySC2 - StarCraft II Learning Environment.
  • DeepMind RL Unplugged - Benchmarks for Offline Reinforcement Learning.
  • Facebook EmbodiedQA - Train embodied agents that can answer questions in environments.
  • Facebook Habitat - A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.
  • Facebook House3D - A Rich and Realistic 3D Environment.
  • Facebook naturalrlenvironment - natural signal Atari environments, introduced in the paper Natural Environment Benchmarks for Reinforcement Learning.
  • Google Research Football - An RL environment based on open-source game Gameplay Football.
  • GVGAI Gym - An OpenAI Gym environment for games written in the Video Game Description Language, including the Generic Video Game Competition framework.
  • gym-doom - Doom environments based on VizDoom.
  • gym-duckietown - Self-driving car simulator for the Duckietown universe.
  • gym-gazebo2 - A toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo.
  • gym-ignition - Experimental OpenAI Gym environments implemented with Ignition Robotics.
  • gym-idsgame - An Abstract Cyber Security Simulation and Markov Game for OpenAI Gym
  • gym-super-mario - 32 levels of original Super Mario Bros.
  • Holodeck - High Fidelity Simulator for Reinforcement Learning and Robotics Research.
  • home-platform - A platform for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context
  • ma-gym - A collection of multi agent environments based on OpenAI gym.
  • mazelab - A customizable framework to create maze and gridworld environments.
  • Meta-World - An open source robotics benchmark for meta- and multi-task reinforcement learning.
  • Microsoft AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research.
  • Microsoft Jericho - A learning environment for man-made Interactive Fiction games.
  • Microsoft Malmö - A platform for Artificial Intelligence experimentation and research built on top of Minecraft.
  • Microsoft MazeExplorer - Customisable 3D environment for assessing generalisation in Reinforcement Learning.
  • Microsoft TextWorld - A text-based game generator and extensible sandbox learning environment for training and testing reinforcement learning (RL) agents.
  • MineRL - MineRL Competition for Sample Efficient Reinforcement Learning.
  • MuJoCo - Advanced physics simulation.
  • OpenAI Coinrun - Code for the environments used in the paper Quantifying Generalization in Reinforcement Learning.
  • OpenAI Gym Retro - Retro Games in Gym.
  • OpenAI Gym Soccer - A multiagent domain featuring continuous state and action spaces.
  • OpenAI Gym - A toolkit for developing and comparing reinforcement learning algorithms.
  • OpenAI Multi-Agent Particle Environment - A simple multi-agent particle world with a continuous observation and discrete action space, along with some basic simulated physics.
  • OpenAI Neural MMO - A Massively Multiagent Game Environment.
  • OpenAI Procgen Benchmark - Procedurally Generated Game-Like Gym Environments.
  • OpenAI Roboschool - Open-source software for robot simulation, integrated with OpenAI Gym.
  • OpenAI RoboSumo - A set of competitive multi-agent environments used in the paper Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments.
  • OpenAI Safety Gym - Tools for accelerating safe exploration research.
  • Personae - RL & SL Methods and Envs For Quantitative Trading.
  • Pommerman - A clone of Bomberman built for AI research.
  • pybullet-gym - Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform
  • PyGame Learning Environment - Reinforcement Learning Environment in Python.
  • RLBench - A large-scale benchmark and learning environment.
  • RLTrader - A cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym.
  • RoboNet - A Dataset for Large-Scale Multi-Robot Learning.
  • rocket-lander - SpaceX Falcon 9 Box2D continuous-action simulation with traditional and AI controllers.
  • Stanford Gibson Environments - Real-World Perception for Embodied Agents.
  • Stanford osim-rl - Reinforcement learning environments with musculoskeletal models.
  • Unity ML-Agents Toolkit - Unity Machine Learning Agents Toolkit.
  • UnityObstableTower - A procedurally generated environment consisting of multiple floors to be solved by a learning agent.
  • VizDoom - Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information.


Check AICrowd for the latest list of major RL competitions





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