Reinforcement learning
Acme, TorchRL & Ray seem nice. Hugging Face Deep Reinforcement Learning Class is great intro.
title: Reinforcement learning#
Acme ↗, TorchRL ↗ & Ray ↗ seem nice. Hugging Face Deep Reinforcement Learning Class ↗ is great intro.
Reinforcement Learning with Neural Radiance Fields ↗ is fascinating.
Links#
- Where to start learning Reinforcement Learning in 2018? ↗
- Reinforcement Learning, An Introduction Book ↗ - Significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. (Web ↗) (Code ↗) (Julia Code ↗) (Video Summary ↗)
- Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, TensorFlow. Exercises and Solutions to accompany Sutton’s Book and David Silver’s course. ↗
- Learning to Learn for Robotic Control - Prof. Pieter Abbeel ↗
- MIT AGI: OpenAI Meta-Learning and Self-Play (Ilya Sutskever) ↗
- Dissecting Reinforcement Learning: Part 1 ↗
- Learning Dexterity (2018) ↗
- Dopamine ↗ - Research framework for fast prototyping of reinforcement learning algorithms.
- Spinning Up in Deep RL ↗ - Educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). (Docs ↗) (HN ↗) (Code ↗)
- Advanced Deep Learning & Reinforcement Learning Course (2018) ↗
- OpenAI Gym ↗ - Toolkit for developing and comparing reinforcement learning algorithms.
- Hands-On Reinforcement Learning With Python book ↗
- David Silver Reinforcement learning ↗ - Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
- Paper Collection of Multi-Agent Reinforcement Learning (MARL) ↗
- MARL (Multi-Agent Reinforcement Learning Experiments) ↗
- RLlib ↗ - Open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications.
- Stable Baselines ↗ - Set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines.
- pytorch-a3c ↗ - PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from “Asynchronous Methods for Deep Reinforcement Learning”.
- The Power of Self-Learning Systems (2019) ↗
- Awesome Self-Supervised Learning ↗
- PlaNet ↗ - Deep Planning Network: Control from pixels by latent planning with learned dynamics.
- Learning to Paint ↗ - Painting AI that can reproduce paintings stroke by stroke using deep reinforcement learning.
- Self-Supervised Learning ↗ (HN ↗)
- RL Baselines Zoo ↗ - Collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
- bsuite ↗ - Collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent.
- OpenSpiel ↗ - Collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
- Stochastic Lower Bound Optimization ↗ - Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees.
- KataGo ↗ - Research and experimentation with self-play training in Go.
- Catalyst ↗ - Reproducible and fast DL & RL.
- The Mathematics of AlphaGo (2019) ↗
- Value Prediction Network (2017) ↗
- Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model (2019) ↗ (Reddit ↗) (Article ↗)
- BCQ ↗ - PyTorch implementation of BCQ for “Off-Policy Deep Reinforcement Learning without Exploration”.
- Reinforcement Learning: Theory and Algorithms ↗ (HN ↗)
- TorchBeast ↗ - PyTorch Platform for Distributed RL.
- The Promise of Hierarchical Reinforcement Learning (2019) ↗
- rlpyt ↗ - Reinforcement Learning in PyTorch.
- Accelerated Methods for Deep Reinforcement Learning ↗
- Programmatically interpretable reinforcement learning (2020) ↗
- Curriculum for Reinforcement Learning (2020) ↗
- RLax ↗ - Library built on top of JAX that exposes useful building blocks for implementing reinforcement learning agents.
- Curated list of awesome imitation learning resources and publications ↗
- Structural implementation of RL key algorithms ↗
- DeepRLHacks ↗ - Hacks for training RL systems from John Schulman’s lecture at Deep RL Bootcamp.
- Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford University, MIT, UC Berkeley ↗
- PyTorch implementation of soft actor critic ↗
- Tutorial on Deep Reinforcement Learning in PyTorch ↗
- prob_mbrl ↗ - Library of probabilistic model based RL algorithms in pytorch.
- PhoenixGo ↗ - Go AI program which implements the AlphaGo Zero paper.
- TensorTrade ↗ - Trade Efficiently with Reinforcement Learning.
- En-Lightning Reinforcement Learning (2020) ↗ - Building a DQN with PyTorch Lightning.
- Transformer Reinforcement Learning ↗ - Train transformer language models with reinforcement learning.
- David Silver - Deep Reinforcement Learning from AlphaGo to AlphaStar (2020) ↗
- AlphaZero.jl ↗ - Generic, simple and fast implementation of Deepmind’s AlphaZero algorithm. (HN ↗)
- Multi-Agent Particle Environment ↗
- CURL: Contrastive Unsupervised Representations for Reinforcement Learning (2020) ↗ (Code ↗)
- Maria-Florina Balcan’s publications ↗
- An Optimistic Perspective on Offline Reinforcement Learning (2020) ↗
- Offline Reinforcement Learning: How Conservative Algorithms Can Enable New Applications (2020) ↗
- TensorSwarm ↗ - Framework for reinforcement learning of robot swarms.
- Learning with Random Learning Rates in PyTorch ↗
- Continual Learning Literature ↗
- Using Reinforcement Learning in the Algorithmic Trading Problem (2020) ↗ (HN ↗)
- Unsupervised Meta-Learning: Learning to Learn without Supervision (2020) ↗
- metric-learn ↗ - Metric Learning in Python.
- Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels ↗ (Code ↗)
- Reinforcement Learning Zoo ↗ - Collection of the most practical reinforcement learning algorithms, frameworks and applications.
- The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies (2020) ↗ (Paper ↗) (Twitter ↗)
- mentalRL ↗ - A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry.
- Reinforcement Learning With TicTacToe ↗
- Coach ↗ - Python reinforcement learning framework containing implementation of many state-of-the-art algorithms.
- Reinforcement Learning with Convex Constraints (2019) ↗ (Code ↗)
- Acme: A new framework for distributed reinforcement learning | DeepMind (2020) ↗ (Code ↗) (Intro ↗)
- Slime Volleyball Gym Environment ↗ - Simple OpenAI Gym environment for single and multi-agent reinforcement learning.
- References on Optimal Control, Reinforcement Learning and Motion Planning ↗
- NetHack Learning Environment (NLE) ↗ - Reinforcement Learning environment based on NetHack 3.6.
- RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real (2020) ↗
- MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library (2020) ↗
- Minimalistic Gridworld Environment (MiniGrid) ↗
- Meta-Learning Curiosity Algorithms ↗
- Reinforcement Learning in Swift ↗
- dm_env ↗ - DeepMind RL Environment API.
- SURREAL ↗ - Fully integrated framework that runs state-of-the-art distributed reinforcement learning (RL) algorithms.
- Suggestions of good RL courses (2020) ↗
- Reinforcement Learning Under Moral Uncertainty (2020) ↗ (Reddit ↗) (Code ↗)
- Go-Explore: a New Approach for Hard-Exploration Problems (2019) ↗ (Code ↗)
- Neural Architecture Search (2020) ↗
- Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks ↗
- Tonic ↗ - Deep reinforcement learning library.
- Model Based Reinforcement Learning Benchmarking Library (MBBL) ↗
- TF-Agents ↗ - Reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
- Reinforcement Learning Specialization by University of Alberta ↗
- Optax ↗ - Gradient processing and optimization library for JAX.
- Chex ↗ - Library of utilities for helping to write reliable JAX code.
- Reinforcement Learning for Combinatorial Optimization: A Survey (2020) ↗
- GenRL ↗ - PyTorch reinforcement learning library centered around reproducible and generalizable algorithm implementations. (HN ↗) (Docs ↗) (Tutorials ↗) (Reddit ↗)
- Stable Baselines3 ↗ - PyTorch version of Stable Baselines, improved implementations of reinforcement learning algorithms.
- Minigo ↗ - Minimalist Go engine modeled after AlphaGo Zero, built on MuGo.
- Reinforcement learning, non-Markov environments, and memory (2020) ↗
- Mathy ↗ - Platform for using computer algebra systems to solve math problems step-by-step with reinforcement learning. (Code ↗)
- Multi-Agent Resource Optimization (MARO) ↗ - Instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization.
- Homer: Provable Exploration in Reinforcement Learning (2020) ↗
- RLCard ↗ - Toolkit for Reinforcement Learning in Card Games.
- Deep Reinforcement Learning Course (2020) ↗ (Code ↗)
- GridRoyale ↗ - Life simulation for exploring social dynamics. (HN ↗)
- TorchRL ↗ - PyTorch Implementation of Reinforcement Learning Algorithms.
- Reinforcement learning is supervised learning on optimized data (2020) ↗ (HN ↗)
- Deep Reinforcement Learning Algorithms ↗
- Introduction to Reinforcement Learning (2020) ↗ (Code ↗)
- AI safety gridworlds ↗ - Suite of reinforcement learning environments illustrating various safety properties of intelligent agents.
- RL and Deep-RL implementations ↗
- You don’t need reinforcement learning when you have basic physics (2020) ↗ (HN ↗)
- TensorLayer ↗ - Deep Learning and Reinforcement Learning Library for Scientists and Engineers. (Docs ↗)
- FitML ↗ - Collection of python Machine Learning articles and examples.
- Notes and scripts for SC2LE released by DeepMind and Blizzard ↗
- PFRL ↗ - PyTorch-based deep reinforcement learning library.
- Deep Reinforcement Learning Papers ↗
- ChainerRL ↗ - Deep reinforcement learning library built on top of Chainer.
- RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments ↗
- Best Reinforcement Learning Tutorials, Examples, Projects, and Courses (2020) ↗
- EvoStrat ↗ - Library that makes Evolutionary Strategies (ES) simple to use.
- Alpha Zero Boosted ↗ - “build to learn” implementation of the Alpha Zero algorithm written in Python that uses LightGBM (Gradient Boosted Decision Trees) in place of a Deep Neural Network for value/policy functions.
- XingTian ↗ - Componentized library for the development and verification of reinforcement learning algorithms.
- Theoretical Foundations of Reinforcement Learning (2020) ↗
- mazelab ↗ - Customizable framework to create maze and gridworld environments.
- Addressing Function Approximation Error in Actor-Critic Methods ↗ - PyTorch implementation of Twin Delayed Deep Deterministic Policy Gradients (TD3).
- Discovering Reinforcement Learning Algorithms (2020) ↗
- Data-Efficient Reinforcement Learning with Self-Predictive Representations ↗
- DeepMind Lab2D ↗ - Flexible and fast engine for rapidly creating 2D environments. Built for RL, and well suited for the needs of multi-agent research. (Paper ↗) (HN ↗)
- Understanding RL Vision (2020) ↗
- PettingZoo ↗ - Python library for conducting research in multi-agent reinforcement learning. It’s akin to a multi-agent version of OpenAI’s Gym library.
- DeepMind Hard Eight Tasks ↗ - Set of 8 diverse machine-learning tasks that require exploration in partially observable environments to solve.
- TetrisRL ↗ - Tetris environment to train machine learning agents.
- Deep Reinforcement Learning: Pong from Pixels (2016) ↗
- dm_env_rpc ↗ - Networking protocol for agent-environment communication.
- PHYRE ↗ - Benchmark for physical reasoning. (Web ↗)
- SuperSuit ↗ - Easy-to-use micro-wrappers for Gym and PettingZoo based RL Environments.
- ViZDoom ↗ - Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information. (Web ↗)
- Reinforcement Learning at Microsoft ↗
- banditml ↗ - Lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.
- SUMO-RL ↗ - Provides a simple interface to instantiate Reinforcement Learning environments with SUMO for Traffic Signal Control.
- PyGeneses ↗ - PyTorch based DeepRL framework to train and study artificial species in bio-inspired environments. (Docs ↗) (Article ↗)
- Lessons Learned Reproducing a Deep Reinforcement Learning Paper (2018) ↗
- CompilerGym ↗ - Reinforcement learning toolkit for compiler optimizations. (Docs ↗) (HN ↗)
- Introduction to Reinforcement Learning with David Silver ↗
- MuZero General ↗ - Commented and documented implementation of MuZero based on the Google DeepMind paper (Nov 2019) and the associated pseudocode.
- Deep Reinforcement Learning Hands-On (2020) ↗ (Code ↗)
- ReBeL ↗ - Algorithm that generalizes the paradigm of self-play reinforcement learning and search to imperfect-information games.
- NEAT Gym ↗ - Learn OpenAI Gym environments using NEAT.
- RLStructures ↗ - Library to facilitate the implementation of new reinforcement learning algorithms.
- FinRL ↗ - Deep Reinforcement Learning Library for Quantitative Finance. (HN ↗)
- ReAgent ↗ - Platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.). (Docs ↗)
- Deep Reinforcement Learning Algorithms ↗
- CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning ↗
- minimalRL PyTorch ↗ - Implementations of basic RL algorithms with minimal lines of code.
- Awesome RL Competitions ↗
- PyGame Learning Environment ↗ - Reinforcement Learning Environment in Python.
- OpenAI PLE environment ↗ - Learning environment, mimicking the Arcade Learning Environment interface.
- h-baselines ↗ - High-performing hierarchical reinforcement learning models and algorithms.
- AI Habitat ↗ - Simulation platform for research in Embodied AI. (Habitat Challenge 2020 Code ↗)
- Fundamentals of Multiagent Systems (2010) ↗
- CleanRL ↗ - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features.
- Rainbow is all you need ↗ - Step-by-step tutorial from DQN to Rainbow.
- MTEnv ↗ - MultiTask Environments for Reinforcement Learning.
- Mastering Atari with Discrete World Models (2021) ↗
- Proto-RL: Reinforcement Learning with Prototypical Representations ↗
- Task-Agnostic Morphology Optimization (2021) ↗ (Code ↗)
- MADRL ↗ - Code for multi-agent deep reinforcement learning.
- Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings (2021) ↗ (Code ↗)
- Self-supervised learning: The dark matter of intelligence (2021) ↗ (Tweet ↗)
- Examples of RL applied to problems that aren’t gaming/robotics? (2021) ↗
- Self-Supervised Policy Adaptation during Deployment (2020) ↗ (Reddit ↗)
- Self-Supervised Learning - Yann LeCun (2019) ↗
- Reinforcement Learning: Introduction by Sutton and Barto ↗
- Debugging Reinforcement Learning Systems (2021) ↗
- Mastering Real-Time Strategy Games with Deep Reinforcement Learning: Mere Mortal Edition (2021) ↗
- adeptRL ↗ - Reinforcement learning framework to accelerate research.
- OpenAI Baselines ↗ - Set of high-quality implementations of reinforcement learning algorithms.
- Jax (Flax) RL ↗ - Jax (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
- Markov Decision Processes (MDPs) - Structuring a Reinforcement Learning Problem (2018) ↗
- Deep Reinforcement Learning Berkeley Course ↗ (Code ↗) (GitHub ↗)
- Awesome Offline RL ↗ - Collection of research and review papers for offline reinforcement learning.
- Podracer architectures for scalable Reinforcement Learning (2021) ↗ (Tweet ↗)
- RL Baselines3 Zoo ↗ - Training Framework for Stable Baselines3 Reinforcement Learning Agents.
- Awesome RL environments ↗
- Awesome Deep RL ↗
- Large collection of machine learning / RF paper notes ↗
- Ecole ↗ - Extensible Combinatorial Optimization Learning Environments. (Web ↗)
- MBRL-Lib ↗ - Library for Model Based RL.
- Towards a Theory of Generalization in Reinforcement Learning (2021) ↗
- Evolving Reinforcement Learning Algorithms (2021) ↗
- Model-Based RL for Decentralized Multi-agent Navigation (2021) ↗
- Mastering Atari with Discrete World Models (2021) ↗ (Code ↗) (Code ↗)
- RoboDesk ↗ - Multi-Task Reinforcement Learning Benchmark.
- ReinforcementLearning.jl ↗ - Reinforcement learning package for Julia. (Web ↗)
- Improving Exploration in Soft-Actor-Critic with Normalizing Flows Policies (2019) ↗ (Code ↗)
- Cherry ↗ - PyTorch Library for Reinforcement Learning Research.
- Decision Transformer: Reinforcement Learning via Sequence Modeling (2021) ↗ (Reddit ↗) (Reddit ↗)
- Reinforcement Learning Tricks, Index ↗
- CS234: Reinforcement Learning Course ↗ (Code ↗)
- Decision Transformer: Reinforcement Learning via Sequence Modeling (2021) ↗ (Code ↗)
- UC Berkeley Robot Learning Lab ↗
- lifelong_rl ↗ - PyTorch implementations of RL algorithms.
- Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation (2021) ↗ (Code ↗)
- Yann LeCun | The Energy-Based Learning Model (2021) ↗
- Lil’Log ↗ - Blog about RL.
- PyTorch implementation of reinforcement learning algorithms ↗
- D4RL: Datasets for Deep Data-Driven Reinforcement Learning ↗
- Meta-World ↗ - Open source robotics benchmark for meta- and multi-task reinforcement learning. (Web ↗)
- garage ↗ - Toolkit for reproducible reinforcement learning research.
- Reinforcement Learning as One Big Sequence Modeling Problem (2021) ↗
- David Silver’s UCL Course on RL ↗
- Mava ↗ - Research framework for distributed multi-agent reinforcement learning. (Paper ↗)
- Reinforcement Learning Examples ↗ - Policy Gradients, PPO+GAE, and DDQN Using OpenAI Gym and PyTorch.
- Hierarchical Reinforcement Learning by Discovering Intrinsic Options ↗ (Code ↗)
- BASALT: A Benchmark for Learning from Human Feedback (2021) ↗ (Tweet ↗)
- BRAX ↗ - Massively parallel rigidbody physics simulation on accelerator hardware.
- Towards Deeper Deep Reinforcement Learning (2021) ↗
- Learning Invariant Representations for Reinforcement Learning without Reconstruction ↗
- Python MARL ↗ - Python Multi-Agent Reinforcement Learning framework.
- Sample Factory ↗ - High throughput asynchronous reinforcement learning.
- Generally capable agents emerge from open-ended play (2021) ↗ (HN ↗)
- Leveraging Procedural Generation to Benchmark Reinforcement Learning (2020) ↗ (Code ↗)
- Intro to Advanced Actor-Critic Methods: Reinforcement Learning Course (2021) ↗
- Tianshou ↗ - Elegant PyTorch deep reinforcement learning library. (Docs ↗)
- Reinforcement Learning Generator-Evaluator Architecture for Question Generation ↗
- AlphaGPU ↗ - Alphazero on GPU thanks to CUDA.jl.
- Policy Gradient Methods for Reinforcement Learning with Function Approximation (1999) ↗
- For a beginner, what are the most influential papers in the history of RL? (2021) ↗
- rliable ↗ - Open-source library for reliable evaluation on reinforcement learning and machine learnings benchmarks.
- d3rlpy ↗ - Offline deep reinforcement learning library. (Web ↗)
- Why You Shouldn’t Use Reinforcement Learning (2021) ↗
- Reinforcement Learning with Augmented Data ↗ (Code ↗)
- Greedy AI agents learn to cooperate (2021) ↗ (HN ↗)
- Spice.ai ↗ - Open source, portable runtime for training and using deep learning on time series data. (HN ↗)
- Reinforcement Learning Lecture Series 2021 | DeepMind ↗ (Videos ↗) (Tweet ↗) (Reddit ↗)
- PPO-PyTorch ↗ - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch.
- rlberry ↗ - Easy-to-use reinforcement learning library for research and education.
- SEED RL ↗ - Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED’s architecture.
- MiniHack ↗ - Sandbox for Open-Ended Reinforcement Learning Research.
- An Outsider’s Tour of Reinforcement Learning (2018) ↗
- Mastering Atari with Discrete World Models (2020) ↗ (Code ↗)
- Falken ↗ - Provides developers with a service that allows them to train AI that can play their games.
- irl-imitation ↗ - Implementation of Inverse Reinforcement Learning (IRL) algorithms in python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL.
- Best RL papers from the past year or two (2021) ↗
- Recurrent Model-Free RL is a Strong Baseline for Many POMDPs (2021) ↗
- Godot RL Agents ↗ (Reddit ↗)
- SaLinA: Sequential Learning of Agents (2021) ↗ - Flexible and Simple Library for Learning Sequential Agents (including Reinforcement Learning). (Code ↗) (Tweet ↗)
- EnvironmentLogger ↗ - Tool for recording RL trajectories.
- DrQ-v2 ↗ - Improved Data-Augmented Reinforcement Learning.
- Arcade Learning Environment (ALE) ↗ - Simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games.
- ML Mentorship: Some Q/A about RL (2021) ↗
- RLs ↗ - Reinforcement Learning Algorithms Based on PyTorch.
- DeepMind Alchemy environment ↗ - Meta-reinforcement learning benchmark.
- gym-hybrid ↗ - Collection of environment for reinforcement learning task possessing discrete-continuous hybrid action space.
- Simple PyTorch Implementations of Deep RL Algorithms for Continuous Control Research ↗
- Learning to Ground Multi-Agent Communication with Autoencoders (2021) ↗
- Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives (2021) ↗ (Code ↗)
- Unsupervised Reinforcement Learning Benchmark (URLB) ↗
- Mastering Atari Games with Limited Data (2021) ↗ (Code ↗)
- RL Starter Files ↗ - RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code.
- JORLDY ↗ - Open Source Reinforcement Learning Framework.
- sinergym ↗ - Gym environment for building simulation and control using reinforcement learning.
- MetaDrive ↗ - Composing Diverse Driving Scenarios for Generalizable RL.
- Crafter ↗ - Benchmarking the Spectrum of Agent Capabilities.
- RLDS ↗ - Reinforcement Learning Datasets.
- Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability (2021) ↗ (Paper ↗)
- Offline Reinforcement Learning: BayLearn 2021 Keynote Talk ↗
- Baby Robot’s Guide to Reinforcement Learning ↗
- Learning Off-Policy with Online Planning (2020) ↗ (Code ↗)
- f-IRL: Inverse Reinforcement Learning via State Marginal Matching (2020) ↗ (Code ↗)
- TD3+BC ↗ - Minimalist Approach to Offline Reinforcement Learning.
- Reinforcement Learning Course Materials ↗
- On the Expressivity of Markov Reward (2021) ↗ (Tweet ↗)
- Isaac Gym Benchmark Environments ↗ - Contains example RL environments for the NVIDIA Isaac Gym high performance environments.
- Offline Reinforcement Learning with Implicit Q-Learning (2021) ↗ (Code ↗)
- A Survey of Generalisation in Deep Reinforcement Learning (2021) ↗ (Tweet ↗)
- Permutation-Invariant Neural Networks for Reinforcement Learning (2021) ↗
- EnvPool ↗ - C++-based high-performance parallel environment execution engine for general RL environments. (Docs ↗)
- Magi RL library in JAX ↗
- WarpDrive ↗ - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU.
- Embodied ↗ - Fast reinforcement learning research.
- Permutation-Invariant Neural Networks for Reinforcement Learning (2021) ↗ (HN ↗)
- Only RL setting worth studying is the MDP (2021) ↗ (Tweet ↗)
- Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy (2020) ↗ (Code ↗)
- Deep Reinforcement Learning Algorithms with PyTorch ↗
- MARL-Baselines3 ↗ - Multi-Agent Reinforcement Learning with Stable-Baselines3.
- ALF ↗ - Reinforcement learning framework emphasizing on the flexibility and easiness of implementing complex algorithms involving many different components.
- On the Practical Consistency of Meta-Reinforcement Learning Algorithms (2021) ↗ (Tweet ↗)
- Awesome Reinforcement Learning for Cyber Security ↗
- Balloon Learning Environment ↗ - Flying stratospheric balloons with deep reinforcement learning.
- The potential of transformers in reinforcement learning (2021) ↗ (HN ↗)
- rvs ↗ - Reinforcement Learning via Supervised Learning.
- RLHive ↗ - Framework designed to facilitate research in reinforcement learning.
- Gym-ANM ↗ - Design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.
- Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation (2020) ↗
- Deep Reinforcement Learning for Keras ↗
- DeepRL ↗ - Modularized Implementation of Deep RL Algorithms in PyTorch.
- Deep Reinforcement Learning Toolkit for Cryptocurrencies ↗ - Record and replay cryptocurrency limit order book data & train a DDQN agent.
- Multi-View Reinforcement Learning (2019) ↗ (Code ↗)
- Mean Field Multi-Agent Reinforcement Learning (2019) ↗ (Code ↗)
- An Optimistic Perspective on Offline Reinforcement Learning (2020) ↗ (Code ↗)
- Deep Inverse Reinforcement Learning ↗ (Code ↗)
- RLMeta ↗ - Light-weight flexible framework for Distributed Reinforcement Learning Research.
- HandyRL ↗ - Handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
- Simple random search provides a competitive approach to reinforcement learning (2018) ↗ (Code ↗)
- Reinforcement Learning as a fine-tuning paradigm (2022) ↗
- MTRL ↗ - Multi Task RL Baselines.
- MAgent ↗ - Library for creating 2D environments with very large numbers of agents for conducting research in Multi-Agent Reinforcement Learning.
- RLkit ↗ - Reinforcement learning framework and algorithms implemented in PyTorch.
- Can Wikipedia Help Offline Reinforcement Learning? (2022) ↗ (Code ↗)
- Don’t Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning (2021) ↗ (Code ↗)
- Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning (2021) ↗ (Code ↗)
- Representation Learning for Reinforcement Learning ↗
- Deep Reinforcement Learning in The Real World ↗
- Solving NP-Hard Problems on Graphs with Extended AlphaGo Zero (2019) ↗ (Code ↗)
- The Value Equivalence Principle for Model-Based Reinforcement Learning (2020) ↗ (Code ↗)
- ai-traineree ↗ - PyTorch agents and tools for (Deep) Reinforcement Learning.
- RL Games: High performance RL library ↗
- MuZero’s first step from research into the real world (2022) ↗ (HN ↗)
- Isaac-ManipulaRL ↗ - Manipulator Reinforcement Learning based on Isaac-gym.
- coax ↗ - Plug-n-Play Reinforcement Learning in Python with OpenAI Gym and JAX.
- Implementation of Distributed Reinforcement Learning with TensorFlow ↗
- Gold ↗ - Reinforcement Learning in Go.
- MetaGym ↗ - Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.
- Melting Pot ↗ - Suite of test scenarios for multi-agent reinforcement learning.
- CQL ↗ - Simple and modular implementation of the Conservative Q Learning and Soft Actor Critic algorithm in PyTorch.
- Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments (2017) ↗ (Code ↗)
- TorchRL ↗ - Modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
- The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games ↗ (Code ↗)
- Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning (2021) ↗ (Code ↗)
- or-gym ↗ - Environments for OR and RL Research.
- AI-Optimizer ↗ - Next generation deep reinforcement learning tookit.
- SuperSonic ↗ - Automating reinforcement learning architecture design for code optimization.
- panda-gym ↗ - OpenAI/gym robotic environments based on PyBullet physics engine.
- Huskarl ↗ - Deep Reinforcement Learning Framework + Algorithms.
- Resources and material for an internal course on Reinforcement Learning ↗
- MO-Gym: Multi-Objective Reinforcement Learning Environments ↗
- DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills (2018) ↗ (Code ↗)
- SC2RL ↗ - Reinforcement Learning + Starcraft 2.
- raylab ↗ - Reinforcement learning algorithms in RLlib and PyTorch.
- Hugging Face Deep Reinforcement Learning Class ↗
- OpenAI Gym environment designed for training RL agents to control the flight of a two-dimensional drone ↗
- Hands-on Reinforcement Learning course ↗
- Rocket League Gym ↗ - Gym-like environment for Reinforcement Learning in Rocket League.
- SLM Lab ↗ - Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book “Foundations of Deep Reinforcement Learning”.
- Safe Reinforcement Learning Baseline ↗
- Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning ↗
- Understanding Game-Playing Agents with Natural Language Annotations (2022) ↗ (Tweet ↗)
- Learning to Brachiate via Simplified Model Imitation (2022) ↗ (Code ↗)
- DeepMind: A Generalist Agent (2022) ↗ (HN ↗) (Tweet ↗)
- Alpha Zero and Monte Carlo Tree Search ↗ - Absolute most basic example of AlphaZero and Monte Carlo Tree Search. (Code ↗)
- Scalable Deep Reinforcement Learning Algorithms for Mean Field Games (2022) ↗
- RL4Rec ↗ - Toolkit of Reinforcement Learning based Recommendation.
- Brain Agent ↗ - Large-Scale and Multi-Task Agent Learning.
- Julia Reinforcement Learning Algorithms ↗
- Border ↗ - Reinforcement learning library in Rust.
- Multi-Agent Reinforcement Learning is a Sequence Modeling Problem (2022) ↗ (HN ↗)
- Reinforcement Learning with Neural Radiance Fields (2022) ↗ (Web ↗)
- Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs (2022) ↗ (Code ↗)
- Offline RL for Natural Language Generation with Implicit Language Q Learning ↗ (Code ↗)
- Flow ↗ - Computational framework for deep RL and control experiments for traffic microsimulation.
- AlgebraicRL.jl ↗ - Julia library for composing Markov decision processes (MDPs) and their agents compositionally.