Awesome Safe MARL 
A (very subjective) curated list of Safe Multi-agent Reinforcement Learning resources.
Preliminaries
Constrained Optimization
TODO
Control Theory
TODO
MBRL
TODO
Safe RL
-
Constrained Policy Optimization, Achiam et al, 2017. Algorithm: CPO.
-
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation, Sootla et al, 2022. Algorithm: Saute MDP augmentation.
Graph Theory
TODO
Federated Learning
TODO
MARL
Books
- Part V of Algorithms for Decision Making by Mykel J. Kochenderfer, Tim A. Wheeler and Kyle H. Wray
- Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations by Yoav Shoham and Kevin Leyton-Brown
- Multi-Agent Coordination: A Reinforcement Learning Approach by Arup
Kumar Sadhu and Amit Konar
💵 - Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments by Minghui Zhu and Sonia Martinez
💵
Papers (survey)
- Multi-agent Reinforcement Learning: An Overview, Busoniu et al, 2010.
- Multi-agent deep reinforcement learning: a survey, Sven Gronauer and Klaus Diepold, 2021.
- A Survey of Multi-Agent Reinforcement Learning with Communication, Zhu et al, 2022.
Papers (research)
POMDP for Multiple Agents
TODO
Value Factorization
- Multiagent Cooperation and Competition with Deep Reinforcement Learning, Tampuu et al, 2015.
- Value-Decomposition Networks For Cooperative Multi-Agent Learning, Sunehag et al, 2017.
- QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning, Rashid et al, 2018. Algorithm: QMIX.
- QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning, Son et al, 2019.
- QPLEX: Duplex Dueling Multi-Agent Q-Learning, Wang et al, 2020.
Policy Gradient
- Counterfactual Multi-Agent Policy Gradients, Foerster et al, 2018.
- Distributed Multi-Agent Reinforcement Learning by Actor-Critic Method, P. Heredia, S. Mou, 2019.
Communication
- Learning to Communicate with Deep Multi-Agent Reinforcement Learning, Foerster et al, 2016.
- Learning Multiagent Communication with Backpropagation, Sukhbaatar et al, 2016.
- TarMAC: Targeted Multi-Agent Communication, Das et al, 2019.
- Learning to Ground Multi-Agent Communication with Autoencoders, Lin et al, 2021.
- Differentially Private and Communication Efficient Collaborative Learning, Ding et al, 2021.
DLQR
- Distributed Q-Learning for Dynamically Decoupled Systems, Siavash Alemzadeh, Mehran Mesbahi, 2018.
- D3PI: Data-Driven Distributed Policy Iteration for Homogeneous Interconnected Systems, Alemzadeh et al, 2021.
- Data-Driven Distributed Optimal Consensus Control for Unknown Multiagent Systems With Input-Delay, Zhang et al, 2018.
- Distributed Q-Learning with State Tracking for Multi-agent Networked Control, Wang et al, 2020.
- Distributed Adaptive Linear Quadratic Control using Distributed Reinforcement Learning, Daniel Goerges, 2019.
- Distributed Linear-Quadratic Control with Graph Neural Networks, Fernando Gama, Somayeh Sojoudi, 2021.
- Distributed Online Linear Quadratic Control for Linear Time-invariant Systems, Ting-Jui Chang, Shahin Shahrampour, 2020.
- Learning Distributed Stabilizing Controllers for Multi-Agent Systems, Jing et al, 2021.
Vehicle Platoon
- Distributed Nonlinear Model Predictive Control for Connected Autonomous Electric Vehicles Platoon with Distance-Dependent Air Drag Formulation, Caiazzo et al, 2021.
Engineering
Building Multi-agent Environments
- Multi-Agent Learning Environments, blog post by Lukas Schäfer
- PettingZoo Neurips'21 paper
- PettingZoo Documentation
- ma-gym with minimal-marl, set of baselines for vanilla MARL problems by Anurag Koul
- Ray Multi-Agent and Hierarchical Environments