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awesome-deep-rl
A curated list of awesome Deep Reinforcement Learning resources.
https://github.com/kengz/awesome-deep-rl
Last synced: 6 days ago
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Environments
- RoboNet - A Dataset for Large-Scale Multi-Robot Learning.
- 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
- 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 pycolab - A highly-customisable gridworld game engine with some batteries included.
- Facebook EmbodiedQA - Train embodied agents that can answer questions in environments.
- 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.
- ma-gym - A collection of multi agent environments based on OpenAI gym.
- mazelab - A customizable framework to create maze and gridworld environments.
- 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 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.
- 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.
- RLGym - A python API to treat the game Rocket League as an OpenAI Gym environment.
- RLTrader - A cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym.
- 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.
- UnityObstableTower - A procedurally generated environment consisting of multiple floors to be solved by a learning agent.
- DouZero - A research platform for reinforcement learning in DouDizhu (Chinese poker).
- DeepMind DM Control - The DeepMind Control Suite and Package.
- Unity ML-Agents Toolkit - Unity Machine Learning Agents Toolkit.
- Microsoft Malmö - A platform for Artificial Intelligence experimentation and research built on top of Minecraft.
- DeepMind pycolab - A highly-customisable gridworld game engine with some batteries included.
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Competitions
- 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
- AICrowd
- NeurIPS 2019: MineRL Competition
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Timeline
- Monte Carlo Sampling
- Perceptron
- ASE-ALE — the first Actor-Critic algorithm
- Backpropagation algorithm
- CNNs
- Q-Learning
- TD-Gammon
- SARSA
- Nvidia invented the GPU
- CUDA released
- Arcade Learning Environment (ALE)
- DQN
- DQN human-level control in Atari
- TRPO
- Generalized Advantage Estimation
- Deep Deterministic Policy Gradient (DDPG)
- DoubleDQN
- DuelingDQN
- Prioritized Experience Replay
- TensorFlow
- A3C
- Generative Adversarial Imitation Learning (GAIL)
- PyTorch
- Model-Agnostic Meta-Learning (MAML)
- Distributional RL
- PPO
- OpenAI DotA 2 1:1
- Intrinsic Cusiority Module (ICM)
- Rainbow
- AlphaGo Zero masters Go without human knowledge
- AlphaZero masters Go, Chess and Shogi
- IMPALA
- Go-Explore solved Montezuma’s Revenge
- AlphaZero becomes the strongest player in history for chess, Go, and Shogi
- OpenAI Five defeated world champions at DotA 2
- FTW Quake III Arena Capture the Flag
- AlphaStar: Grandmaster level in StarCraft II
- Emergent Tool Use from Multi-Agent Interaction
- Solving Rubik’s Cube with a Robot Hand
- Agent57 outperforms the standard human benchmark on all 57 Atari games
- MuZero masters Go, chess, shogi and Atari without rules
- Generally capable agents emerge from open-ended play
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- OpenAI DotA 2 1:1
- OpenAI Five defeated world champions at DotA 2
- Emergent Tool Use from Multi-Agent Interaction
- Solving Rubik’s Cube with a Robot Hand
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- CNNs
- DQN human-level control in Atari
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Soft Actor-Critic
- Qt-Opt
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- OpenAI DotA 2 1:1
- OpenAI Five defeated world champions at DotA 2
- Emergent Tool Use from Multi-Agent Interaction
- Solving Rubik’s Cube with a Robot Hand
- DQN human-level control in Atari
- Backpropagation algorithm
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
- Backpropagation algorithm
- DQN human-level control in Atari
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Books
- 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.*
- Algorithms for Reinforcement Learning. *Szepesvari et. al.*
- An Introduction to Deep Reinforcement Learning. *Francois-Lavet et. al.*
- Deep Reinforcement Learning Hands-On. *Lapan*
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Tutorials
- 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
- Sergey Levine CS294 Deep Reinforcement Learning Fall 2017
- Udacity Deep Reinforcement Learning Nanodegree
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Blogs
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Benchmark Results
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Libraries
- 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.
- 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.
- 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.
- RLtools - The fastest deep reinforcement learning library for continuous control, implemented in pure, dependency-free C++ (Python bindings available as well).
- 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.
- UMass Amherst Autonomous Learning Library - A PyTorch library for building deep reinforcement learning agents.
- vel - Bring velocity to deep-learning research.
- DI-engine - A generalized decision intelligence engine. It supports various Deep RL algorithms.
- DeepMind Acme - A research framework for reinforcement learning.
Categories
Sub Categories
Keywords
reinforcement-learning
43
deep-learning
21
deep-reinforcement-learning
19
machine-learning
13
pytorch
10
python
10
tensorflow
9
dqn
8
research
7
openai-gym
7
mujoco
7
artificial-intelligence
7
ai
6
gym
6
simulator
6
robotics
6
computer-vision
6
ppo
5
a2c
4
neural-networks
4
rl
4
paper
4
ddpg
4
advantage-actor-critic
3
actor-critic
3
rl-algorithms
3
sac
3
unreal-engine
3
gym-environment
3
simulation
3
self-driving-car
3
ros
3
imitation-learning
3
atari
3
reinforcement-learning-algorithms
3
policy-gradient
3
data-science
3
openai
3
autonomous-vehicles
2
optimization
2
cross-platform
2
distributed
2
drl
2
soft-actor-critic
2
proximal-policy-optimization
2
pybullet
2
text-based-adventure
2
physics-simulation
2
reinforcement-learning-environments
2
gazebo
2