matthewlanders

matthewlanders's Stars

• chongminggao/EasyRL4Rec

  Language:Jupyter Notebook6112

• koulanurag/ma-gym

  A collection of multi agent environments based on OpenAI gym.

  Language:Python55499

• DaRL-LibSignal/LibSignal

  Language:Python10922

• uoe-agents/smaclite

  The Starcraft Multi-Agent challenge lite

  Language:Python337

• cityflow-project/CityFlow

  A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

  Language:C++785172

• AI4Finance-Foundation/FinRL

  FinRL: Financial Reinforcement Learning. 🔥

  Language:Jupyter Notebook9.7k2.3k

• BY571/Implicit-Q-Learning

  PyTorch implementation of the implicit Q-learning algorithm (IQL)

  Language:Python413

• corl-team/CORL

  High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

  Language:Python45918

• MLD3/OfflineRL_FactoredActions

  [NeurIPS 2022] Leveraging Factored Action Spaces for Efficient Offline RL in Healthcare.

  Language:Jupyter Notebook8

• gwthomas/IQL-PyTorch

  A PyTorch implementation of Implicit Q-Learning

  Language:Python668

• Farama-Foundation/PettingZoo

  An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

  Language:Python2.6k408

• ikostrikov/implicit_q_learning

  Language:Python22638

• clinicalml/gumbel-max-scm

  Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)

  Language:Python4110

• nikhil3456/Deep-Reinforcement-Learning-in-Large-Discrete-Action-Spaces

  PyTorch implementation of the paper "Deep Reinforcement Learning in Large Discrete Action Spaces" (Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, Ben Coppin).

  Language:Jupyter Notebook6510

• jimkon/Deep-Reinforcement-Learning-in-Large-Discrete-Action-Spaces

  Implementation of the algorithm in Python 3, TensorFlow and OpenAI Gym

  Language:Python17254

• suragnair/alpha-zero-general

  A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more

  Language:Jupyter Notebook3.8k1k

• ChangyWen/wolpertinger_ddpg

  Wolpertinger Training with DDPG (Pytorch), Deep Reinforcement Learning in Large Discrete Action Spaces. Multi-GPU/Singer-GPU/CPU compatible.

  Language:Python6416

• YerevaNN/mimic3-benchmarks

  Python suite to construct benchmark machine learning datasets from the MIMIC-III 💊 clinical database.

  Language:Python794328

• automl/CARL

  Benchmarking RL generalization in an interpretable way.

  Language:Python12810

• liuzuxin/FSRL

  🚀 A fast safe reinforcement learning library in PyTorch

  Language:Python15225

• openai/baselines

  OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

  Language:Python15.6k4.9k

• thu-ml/tianshou

  An elegant PyTorch deep reinforcement learning library.

  Language:Python7.8k1.1k

• facebookresearch/minihack

  MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research

  Language:Python47154

• seungeunrho/minimalRL

  Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

  Language:Python2.8k458

• learnables/learn2learn

  A PyTorch Library for Meta-learning Research

  Language:Python2.6k351

• rlworkgroup/garage

  A toolkit for reproducible reinforcement learning research.

  Language:Python1.9k310

• tristandeleu/pytorch-maml-rl

  Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch

  Language:Python816157

• mike-gimelfarb/deep-successor-features-for-transfer

  A reusable framework for successor features for transfer in deep reinforcement learning using keras.

  Language:Python3911

• Farama-Foundation/D4RL-Evaluations

  Language:Python18727

• Farama-Foundation/D4RL

  A collection of reference environments for offline reinforcement learning

  Language:Python1.3k278