Kengz Awesome Deep Rl Save

A curated list of awesome Deep Reinforcement Learning resources.

Project README

Awesome Deep RL Awesome

A curated list of awesome Deep Reinforcement Learning resources.

Contents

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.
  • 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.
  • DI-engine - A generalized decision intelligence engine. It supports various Deep RL algorithms.

Benchmark Results

Environments

  • 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.
  • 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.
  • 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.
  • RLCard - A research platform for reinforcement learning in card games.
  • DouZero - A research platform for reinforcement learning in DouDizhu (Chinese poker).

Competitions

Check AICrowd for the latest list of major RL competitions

Timeline

Books

Tutorials

Blogs

Open Source Agenda is not affiliated with "Kengz Awesome Deep Rl" Project. README Source: kengz/awesome-deep-rl
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