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

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

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in 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.

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 collection of MARL benchmarks based on TorchRL

Multi-Agent Reinforcement Learning (MARL) papers with code

Multi-Agent Reinforcement Learning (MARL) papers

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.

Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG

[NeurIPS 2021] CDS achieves remarkable success in challenging benchmarks SMAC and GRF by balancing sharing and diversity.

A solution for Dynamic Spectrum Management in Mission-Critical UAV Networks using Team Q learning as a Multi-Agent Reinforcement Learning Approach

An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations using Multi Independent Agent Reinforcement Learning

Emergence of complex strategies through multiagent competition

This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.

A Collection of Multi-Agent Reinforcement Learning (MARL) Resources

Implementation of Deep Reinforcement Learning from Self-Play in Imperfect-Information Games (Heinrich and Silver, 2016)

A simple example of how to implement vector based DDPG for MARL tasks using PyTorch and a ML-Agents environment.

Multi-agent reinforcement learning framework

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