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Multi-Agent Reinforcement Learning (MARL) papers with code

MARL Papers with Code

This is a collection of Multi-Agent Reinforcement Learning (MARL) papers with code. I have selected some relatively important papers with open source code and categorized them by time and method.

For MARL papers and MARL resources, please refer to Multi Agent Reinforcement Learning papers and MARL Resources Collection.

I will continually update this repository and I welcome suggestions. (missing important papers, missing categories, invalid links, etc.) This is only a first draft so far and I'll add more resources in the next few months.

This repository is not for commercial purposes.

My email: [email protected]

Overview

Classic Papers

Algorithms

Category Paper Code Accepted at Year
Independent Learning IQL：Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents https://github.com/oxwhirl/pymarl ICML 1993
Value Decomposition VDN：Value-Decomposition Networks For Cooperative Multi-Agent Learning https://github.com/oxwhirl/pymarl AAMAS 2017
Value Decomposition QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning https://github.com/oxwhirl/pymarl ICML 2018
Value Decomposition QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning https://github.com/oxwhirl/pymarl ICML 2019
Policy Gradient COMA：Counterfactual Multi-Agent Policy Gradients https://github.com/oxwhirl/pymarl AAAI 2018
Policy Gradient MADDPG：Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments https://github.com/openai/maddpg NIPS 2017
Communication BiCNet：Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games https://github.com/Coac/CommNet-BiCnet 2017
Communication CommNet：Learning Multiagent Communication with Backpropagation https://github.com/facebookarchive/CommNet NIPS 2016
Communication IC3Net：Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks https://github.com/IC3Net/IC3Net 2018
Communication RIAL/RIDL：Learning to Communicate with Deep Multi-Agent Reinforcement Learning https://github.com/iassael/learning-to-communicate NIPS 2016
Exploration MAVEN：Multi-Agent Variational Exploration https://github.com/starry-sky6688/MARL-Algorithms NIPS 2019

Environments

Environment Paper Code Accepted at Year
StarCraft The StarCraft Multi-Agent Challenge https://github.com/oxwhirl/smac NIPS 2019
StarCraft SMACv2: A New Benchmark for Cooperative Multi-Agent Reinforcement Learning https://github.com/oxwhirl/smacv2 2022
StarCraft Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks https://github.com/uoe-agents/epymarl NIPS 2021
Football Google Research Football: A Novel Reinforcement Learning Environment https://github.com/google-research/football AAAI 2020
PettingZoo PettingZoo: Gym for Multi-Agent Reinforcement Learning https://github.com/Farama-Foundation/PettingZoo NIPS 2021
Melting Pot Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot https://github.com/deepmind/meltingpot ICML 2021
MuJoCo MuJoCo: A physics engine for model-based control https://github.com/deepmind/mujoco IROS 2012
MALib MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning https://github.com/sjtu-marl/malib 2021
MAgent MAgent: A many-agent reinforcement learning platform for artificial collective intelligence https://github.com/Farama-Foundation/MAgent AAAI 2018
Neural MMO Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents https://github.com/openai/neural-mmo 2019
MPE Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments https://github.com/openai/multiagent-particle-envs NIPS 2017
Pommerman Pommerman: A multi-agent playground https://github.com/MultiAgentLearning/playground 2018

Other Papers

Category Paper Code Accepted at Year
Graph Neural Network Multi-Agent Game Abstraction via Graph Attention Neural Network https://github.com/starry-sky6688/MARL-Algorithms AAAI 2020
Curriculum Learning From Few to More: Large-Scale Dynamic Multiagent Curriculum Learning https://github.com/starry-sky6688/MARL-Algorithms AAAI 2020
Curriculum Learning EPC：Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning https://github.com/qian18long/epciclr2020 ICLR 2020
Curriculum Learning/Emergent Emergent Tool Use From Multi-Agent Autocurricula https://github.com/openai/multi-agent-emergence-environments ICLR 2020
Curriculum Learning Cooperative Multi-agent Control using deep reinforcement learning https://github.com/sisl/MADRL AAMAS 2017
Role ROMA: Multi-Agent Reinforcement Learning with Emergent Roles https://github.com/TonghanWang/ROMA ICML 2020
Role RODE: Learning Roles to Decompose Multi-Agent Tasks https://github.com/TonghanWang/RODE ICLR 2021
Opponent Modeling Opponent Modeling in Deep Reinforcement Learning https://github.com/hhexiy/opponent ICML 2016
Selfish Agent M3RL: Mind-aware Multi-agent Management Reinforcement Learning https://github.com/facebookresearch/M3RL ICLR 2019
Communication Emergence of grounded compositional language in multi-agent populations https://github.com/bkgoksel/emergent-language AAAI 2018
Communication Fully decentralized multi-agent reinforcement learning with networked agents https://github.com/cts198859/deeprl_network ICML 2018
Policy Gradient DOP: Off-Policy Multi-Agent Decomposed Policy Gradients https://github.com/TonghanWang/DOP ICLR 2021
Policy Gradient MAAC：Actor-Attention-Critic for Multi-Agent Reinforcement Learning https://github.com/shariqiqbal2810/MAAC ICML 2019
Environment Emergent Complexity via Multi-Agent Competition https://github.com/openai/multiagent-competition ICLR 2018
Exploration EITI/EDTI：Influence-Based Multi-Agent Exploration https://github.com/TonghanWang/EITI-EDTI ICLR 2020
Exploration LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning https://github.com/yalidu/liir NIPS 2019
From Single-Agent to Multi-Agent MAPPO：The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games https://github.com/marlbenchmark/on-policy 2021
Diversity Q-DPP：Multi-Agent Determinantal Q-Learning https://github.com/QDPP-GitHub/QDPP ICML 2020
Ad Hoc Teamwork CollaQ：Multi-Agent Collaboration via Reward Attribution Decomposition https://github.com/facebookresearch/CollaQ 2020
Value Decomposition NDQ: Learning Nearly Decomposable Value Functions Via Communication Minimization https://github.com/TonghanWang/NDQ ICLR 2020
Value Decomposition QPLEX: Duplex Dueling Multi-Agent Q-Learning https://github.com/wjh720/QPLEX ICLR 2021
Self-Play TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning https://github.com/tencent-ailab/TLeague 2020
Transformer UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers https://github.com/hhhusiyi-monash/UPDeT ICLR 2021
Sparse Reward Individual Reward Assisted Multi-Agent Reinforcement Learning https://github.com/MDrW/ICML2022-IRAT ICML 2022
Ad Hoc Open Ad Hoc Teamwork using Graph-based Policy Learning https://github.com/uoe-agents/GPL ICLM 2021
Generalization UNMAS: Multiagent Reinforcement Learningfor Unshaped Cooperative Scenarios https://github.com/James0618/unmas TNNLS 2021

TODO

Citation

If you find this repository useful, please cite our repo:

@misc{chen2021multi,
  author={Chen, Hao},
  title={Multi-Agent Reinforcement Learning Papers with Code},
  year={2021}
  publisher = {GitHub},
  journal = {GitHub Repository},
  howpublished = {\url{https://github.com/TimeBreaker/MARL-papers-with-code}}
}

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