Popular GitHub Repositories for Marl

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

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

? A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)

Concise pytorch implements of MARL algorithms, including MAPPO, MADDPG, MATD3, QMIX and VDN.

Multi-Agent Reinforcement Learning with JAX

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

A collection of MARL benchmarks based on TorchRL

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.

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.

A framework for creating rich, 3D, Minecraft-like single and multi-agent environments for AI research. (Accepted at ICML 2025).

Research platform for Human-in-the-loop learning (HILL) & Multi-Agent Reinforcement Learning (MARL)

A tool for aggregating and plotting MARL experiment data.

demo of multi-agent reinforcement learning algorithms, such as ATT-MADDPG (Modelling the Dynamic Joint Policy of Teammates with Attention Multi-Agent DDPG) and NCC-MARL (Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning).

SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning

applying multi-agent reinforcement learning for highway-merging autonomous vehicles

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

Training of Drone Swarms using StableBaselines3, PettingZoo, AirSim and UE4

Code for the paper "MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response"