SimonRosen173

SimonRosen173's Stars

• anuraghazra/github-readme-stats

  :zap: Dynamically generated stats for your github readmes

  Language:JavaScript70.6k2791.3k23.5k

• openai/spinningup

  An educational resource to help anyone learn deep reinforcement learning.

  Language:Python10.3k2292872.3k

• google-deepmind/pysc2

  StarCraft II Learning Environment

  Language:Python8.1k3472821.2k

• google-deepmind/lab

  A customisable 3D platform for agent-based AI research

  Language:C7.2k4662261.4k

• vwxyzjn/cleanrl

  High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

  Language:Python6k38186678

• Farama-Foundation/PettingZoo

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

  Language:Python2.7k18383423

• eclipse-sumo/sumo

  Eclipse SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation.

  Language:C++2.6k6915.3k1.5k

• oxwhirl/pymarl

  Python Multi-Agent Reinforcement Learning framework

  Language:Python1.9k30131390

• starry-sky6688/MARL-Algorithms

  Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

  Language:Python1.5k15114286

• PufferAI/PufferLib

  Simplifying reinforcement learning for complex game environments

  Language:C1.4k71572

• oxwhirl/smac

  SMAC: The StarCraft Multi-Agent Challenge

  Language:Python1.1k2287230

• Replicable-MARL/MARLlib

  One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

  Language:Python97111155159

• metadriverse/metadrive

  MetaDrive: Open-source driving simulator

  Language:Python82916368110

• instadeepai/jumanji

  🕹️ A diverse suite of scalable reinforcement learning environments in JAX

  Language:Python6651310485

• google-deepmind/meltingpot

  A suite of test scenarios for multi-agent reinforcement learning.

  Language:Python63816110124

• PKU-MARL/HARL

  Official implementation of HARL algorithms based on PyTorch.

  Language:Python55395266

• openai/safety-gym

  Tools for accelerating safe exploration research.

  Language:Python5101320141

• FLAIROx/JaxMARL

  Multi-Agent Reinforcement Learning with JAX

  Language:Python469103989

• marl-book/codebase

  Official code repo for the MARL book (www.marl-book.com)

  Language:Python415141064

• semitable/robotic-warehouse

  Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

  Language:Python32952475

• kenjyoung/MinAtar

  Language:Python29291558

• kandouss/marlgrid

  Gridworld for MARL experiments

  Language:Python1385625

• XuyangCaoUCSD/LeoEM

  A real-time low-Earth-orbit satellite network emulator

  Language:Python693114

• instadeepai/awesome-marl

  A categorised list of Multi-Agent Reinforcemnt Learning (MARL) papers

  471138

• kleinric/csam-template

  Language:TeX15307

• AIRI-Institute/pogema

  POGEMA stands for Partially-Observable Grid Environment for Multiple Agents. This is a grid-based environment that was specifically designed to be flexible, tunable and scalable. It can be tailored to a variety of PO-MAPF settings.

  Language:Python11002

• geraudnt/boolean_composition

  Code for the paper "A Boolean Task Algebra For Reinforcement Learning"

  Language:Python11103

• raillab/composition

  Code for the paper "Composing Value Functions in Reinforcement Learning"

  Language:HTML8202

• instadeepai/IndabaX-SA-2021

  IndabaX-SA-2021

  Language:Jupyter Notebook220

• Michael-Beukman/PythonIntroWorkshop

  Language:Jupyter Notebook110