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.
- DeepMind bsuite
- OpenAI baselines-results
- OpenAI Baselines
- OpenAI Spinning Up
- ray rl-experiments
- rl-baselines-zoo
- SLM Lab
- vel
- What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study
- yarlp
- 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 natural_rl_environment - 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.
- AWS DeepRacer League 2019
- Flatland Challenge 2019
- Kaggle Connect X Competition 2020
- NeurIPS 2019: Animal-AI Olympics
- NeurIPS 2019: Game of Drones
- NeurIPS 2019: Learn to Move - Walk Around
- NeurIPS 2019: MineRL Competition
- NeurIPS 2019: Reconnaissance Blind Chess
- NeurIPS 2019: Robot open-Ended Autonomous Learning
- Unity Obstacle Tower Challenge 2019
Check AICrowd for the latest list of major RL competitions
- 1947: Monte Carlo Sampling
- 1958: Perceptron
- 1959: Temporal Difference Learning
- 1983: ASE-ALE — the first Actor-Critic algorithm
- 1986: Backpropagation algorithm
- 1989: CNNs
- 1989: Q-Learning
- 1991: TD-Gammon
- 1992: REINFORCE
- 1992: Experience Replay
- 1994: SARSA
- 1999: Nvidia invented the GPU
- 2007: CUDA released
- 2012: Arcade Learning Environment (ALE)
- 2013: DQN
- 2015 Feb: DQN human-level control in Atari
- 2015 Feb: TRPO
- 2015 Jun: Generalized Advantage Estimation
- 2015 Sep: Deep Deterministic Policy Gradient (DDPG)
- 2015 Sep: DoubleDQN
- 2015 Nov: DuelingDQN
- 2015 Nov: Prioritized Experience Replay
- 2015 Nov: TensorFlow
- 2016 Feb: A3C
- 2016 Mar: AlphaGo beats Lee Sedol 4-1
- 2016 Jun: OpenAI Gym
- 2016 Jun: Generative Adversarial Imitation Learning (GAIL)
- 2016 Oct: PyTorch
- 2017 Mar: Model-Agnostic Meta-Learning (MAML)
- 2017 Jul: Distributional RL
- 2017 Jul: PPO
- 2017 Aug: OpenAI DotA 2 1:1
- 2017 Aug: Intrinsic Cusiority Module (ICM)
- 2017 Oct: Rainbow
- 2017 Oct: AlphaGo Zero masters Go without human knowledge
- 2017 Dec: AlphaZero masters Go, Chess and Shogi
- 2018 Jan: Soft Actor-Critic
- 2018 Feb: IMPALA
- 2018 Jun: Qt-Opt
- 2018 Nov: Go-Explore solved Montezuma’s Revenge
- 2018 Dec: AlphaZero becomes the strongest player in history for chess, Go, and Shogi
- 2019 Apr: OpenAI Five defeated world champions at DotA 2
- 2019 May: FTW Quake III Arena Capture the Flag
- 2019 Aug: AlphaStar: Grandmaster level in StarCraft II
- 2019 Sep: Emergent Tool Use from Multi-Agent Interaction
- 2019 Oct: Solving Rubik’s Cube with a Robot Hand
- 2020 Mar: Agent57 outperforms the standard human benchmark on all 57 Atari games
- 2020 Nov: AlphaFold for protein folding
- 2020 Dec: MuZero masters Go, chess, shogi and Atari without rules
- 2021 Aug: Generally capable agents emerge from open-ended play
- Algorithms for Reinforcement Learning. Szepesvari et. al.
- An Introduction to Deep Reinforcement Learning. Francois-Lavet et. al.
- Deep Reinforcement Learning Hands-On. Lapan
- Deep Reinforcement Learning in Action. Zai & Brown
- Foundations of Deep Reinforcement Learning. Graesser & Keng
- Grokking Deep Reinforcement Learning. Morales
- Reinforcement Learning: An Introduction. Sutton & Barto.
- Andrew Karpathy Deep Reinforcement Learning: Pong from Pixels
- Arthur Juliani Simple Reinforcement Learning in Tensorflow Series
- Berkeley Deep Reinforcement Learning Course
- David Silver UCL Course on RL 2015
- Deep RL Bootcamp 2017
- DeepMind UCL Deep RL Course 2018
- DeepMind Learning Resources
- dennybritz/reinforcement-learning
- higgsfield/RL-Adventure-2
- higgsfield/RL-Adventure
- The Hugging Face Deep Reinforcement Learning Class 🤗
- MorvanZhou/Reinforcement Learning Methods and Tutorials
- OpenAI Spinning Up
- Sergey Levine CS294 Deep Reinforcement Learning Fall 2017
- Udacity Deep Reinforcement Learning Nanodegree