Awesome Multi-Agent Reinforcement Learning

A curated list of multi-agent reinforcement learning reading material, environments, and code implementations.

Maintainer(s): Filippos Christianos

Contributing

Pull requests are always welcome!

Table of Contents

• Awesome Multi-Agent Reinforcement Learning
• Contributing
• Table of Contents
• Theory & Reading Material
  • Papers
    • Core (must read!)
    • Surveys
    • Cooperative MARL
    • Opponent Modelling
  • Other reading material (blogs, websites, videos)
• Environments
• Algorithm Implementations

Theory & Reading Material

Papers

Core (must read!)

Surveys

Cooperative MARL

Opponent Modelling

Other reading material (blogs, websites, videos)

Environments

• Level-based Foraging - mixed cooperative-competitive game, which focuses on the coordination of the agents involved.
• Multi-Robot Warehouse - A simulated warehouse with robots moving and delivering requested goods.
• StarCraft Multi-agent Challenge - A decentralised micromanagement scenarios built on StarCraft II.
• Multi-agent Particle Environment - A diverse set of 2D tasks involving cooperation and competition between agents.
• Malmö - An environment built on top of Minecraft. Also see MarLÖ (short for Multi-Agent Reinforcement Learning in MalmÖ).
• Derk's Gym - A MOBA-style multi-agent competitive team-based game.
• Flatland - Based on a real-world problem of coordinating a railway traffic infrastructure.
• Neural-MMO - A massively multiagent game environment for training and evaluating intelligent agents.

Algorithm Implementations

• PyMARL - WhiRL's framework for deep multi-agent reinforcement learning and includes implementations of QMIX, COMA, VDN, IQL, and QTRAN (only cooperative MARL).
• Extended-PyMARL - An extension of the above, with the addition of IA2C, IPPO, MADDPG, MAA2C and MAPPO. Also improves the consistency of the implementations for fair comparisons.