Combine transfer learning into reinforcement learning is a hot and interesting field.

The Survey part includes two highly related surveys, one is focused on Single-agent RL, and another is focus on Multiagent RL.

The SMAC-based part is all papers based on "The StarCraft Multi-Agent Challenge" in recent years(2018-2021).

The State/Action Representation part is about the representation work in RL.

The Papers are sorted by time. Any suggestions and pull requests are welcome.

The sharing principle of these references here is for research. If any authors do not want their paper to be listed here, please feel free to contact Bin Chen (Email: [email protected]).

• Survey
• SMAC-based
• State/Action Representation
• To be continued ...

• Transfer Learning in Deep Reinforcement Learning: A Survey by Zhuangdi Zhu, Kaixiang Lin, and Jiayu Zhou. 2021
• A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems by Felipe Leno Da Silva,Anna Helena Reali Costa. JAIR, 2019 中文翻译
• Agents Teaching Agents: A Survey on Inter-agent Transfer Learning by Da Silva.

• The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games by Chao Yu, etc.
• Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment by Tianze Zhou, etc.
• Multi-Agent Collaboration via Reward Attribution Decomposition by Tianjun Zhang, etc. ICLR 2021. 知乎解读
• UPDET: UNIVERSAL MULTI-AGENT REINFORCEMENT LEARNING VIA POLICY DECOUPLING WITH TRANSFORMERS by Siyi Hu etc. ICLR 2021.
• TRANSFER AMONG AGENTS: AN EFFICIENT MULTIAGENT TRANSFER LEARNING FRAMEWORK by TianPei Yang. 2021.
• From Few to More: Large-Scale Dynamic Multiagent Curriculum Learning by Weixun Wang etc. AAAI 2020.
• Multi-Agent Game Abstraction via Graph Attention Neural Network by Yong Liu etc. AAAI 2020.
• RODE: Learning Roles to Decompose Multi-Agent Tasks by Tonghan Wang etc. 2020.
• Transfer Learning Between RTS Combat Scenarios Using Component-Action Deep Reinforcement Learning by Richard Kelly etc. 2020.
• Adaptive Average Exploration in Multi-Agent Reinforcement Learning by Garrett Hall etc. 2020.
• Multi-Agent Feature Learning and Integration for Mixed Cooperative and Competitive Environment by Yaowen Zhang etc. ICTAI 2020.
• Deep Coordination Graphs by Wendelin Bohmer,Vitaly Kurin,Shimon Whiteson. ICML 2020.
• ROMA: Multi-Agent Reinforcement Learning with Emergent Roles by Tonghan Wang etc. ICML 2020.
• Multi-Agent Determinantal Q-Learning by Yaodong Yang etc. ICML 2020.
• QPLEX: DUPLEX DUELING MULTI-AGENT Q-LEARNING by Jianhao Wang etc. 2020.
• Towards Heterogeneous Multi-Agent Reinforcement Learning with Graph Neural Networks by Douglas R. Meneghetti etc. 2020.
• The Emergence of Individuality in Multi-Agent Reinforcement Learning by Jiechuan Jiang etc. 2020.
• Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning by Filippos Christianos etc. 2020.
• RIIT: Rethinking the Importance of Implementation Tricks in Multi-Agent Reinforcement Learning by Jian Hu etc. 2020.
• Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge? by Christian Schroeder de Witt etc. 2020.
• Rethinking Intelligent Behavior as Competitive Games for Handling Adversarial Challenges to Machine Learning by Joseph B etc. Adversary-Aware Learning Techniques and Trends in Cybersecurity 2020.
• BENCHMARKING MULTI-AGENT DEEP REINFORCEMENT LEARNING ALGORITHMS by Chao Yu etc. 2020.
• StarCraft Micromanagement with Reinforcement Learning and Curriculum Transfer Learning by Kun Shao etc. IEEE Transactions on Emerging Topics in Computational Intelligence 2019.
• Graph Embedding Priors for Multi-task Deep Reinforcement Learning by Neev Parikh etc. 2020.
• The StarCraft Multi-Agent Challenge by Mikayel Samvelyan etc. 2019.
• LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning by Yali Du etc. NIPS 2019
• Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning by Wendelin Bohmer etc. 2019.
• MAVEN: Multi-Agent Variational Exploration by Anuj Mahajan etc. 2019.
• Learning to Teach in Cooperative Multiagent Reinforcement Learning by Shayegan, AAAI 2019.
• Multi-Agent Common Knowledge Reinforcement Learning by Christian A etc. 2018.

• Decoupling Value and Policy for Generalization in Reinforcement Learning by Roberta Raileanue etc. 2021.