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Parameter sharing, where each agent independently learns a policy with fully shared parameters between all policies, is a popular baseline method for multi-agent deep reinforcement learning.
Extensive games and the problem of information
H W Kuhn · 1953
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Stochastic games
L. S. Shapley · 1953
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Planning, learning and coordination in multiagent decision processes
Craig Boutilier · 1996
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Supersuit: Simple microwrappers for reinforcement learning environments
J. K Terry, Benjamin Black, and Ananth Hari · 2008
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Pettingzoo: Gym for multi-agent reinforcement learning
J. K Terry, Benjamin Black, Nathaniel Grammel, Mario Jayakumar, Ananth Hari, Ryan Sulivan, Luis Santos, Rodrigo Perez, Caroline Horsch, Clemens Dieffendahl, Niall L Williams, Yashas Lokesh, Ryan Sullivan, and Praveen Ravi · 2009
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Multiplayer support for the arcade learning environment
J. K Terry, Benjamin Black, and Luis Santos · 2009
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Learning to communicate with deep multi-agent reinforcement learning
Jakob Foerster, Ioannis Alexandros Assael, Nando De Freitas, and Shimon Whiteson · 2016
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Xiangxiang Chu and Hangjun Ye · 2017
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Cooperative multi-agent control using deep reinforcement learning
Jayesh K Gupta, Maxim Egorov, and Mykel Kochenderfer · 2017
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Multi-agent actor-critic for mixed cooperative-competitive environments
Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, OpenAI Pieter Abbeel, and Igor Mordatch · 2017
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Qmix: Monotonic value function factorisation for deep multi-agent reinforcement learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder, Gregory Farquhar, Jakob Foerster, and Shimon Whiteson · 2018
Cited alongside, same era.
Mean field multi-agent reinforcement learning
Yaodong Yang, Rui Luo, Minne Li, Ming Zhou, Weinan Zhang, and Jun Wang · 2018
Cited alongside, same era.
Rl baselines3 zoo
Antonin Raffin · 2020
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Is independent learning all you need in the starcraft multi-agent challenge?
Christian Schroeder de Witt, Tarun Gupta, Denys Makoviichuk, Viktor Makoviychuk, Philip HS Torr, Mingfei Sun, and Shimon Whiteson · 2020
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Deep multi-agent reinforcement learning for highway on-ramp merging in mixed traffic
Dong Chen, Zhaojian Li, Yongqiang Wang, Longsheng Jiang, and Yue Wang · 2021
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Facmac: Factored multi-agent centralised policy gradients
Bei Peng, Tabish Rashid, Christian Schroeder de Witt, Pierre-Alexandre Kamienny, Philip Torr, Wendelin Boehmer, and Shimon Whiteson · 2021
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Stable-baselines3: Reliable reinforcement learning implementations
Antonin Raffin, Ashley Hill, Adam Gleave, Anssi Kanervisto, Maximilian Ernestus, and Noah Dormann · 2021
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Magent: A many-agent reinforcement learning platform for artificial collective intelligence
Lianmin Zheng, Jiacheng Yang, Han Cai, Ming Zhou, Weinan Zhang, Jun Wang, and Yong Yu · 2018
Cited alongside, same era.
The starcraft multi-agent challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder De Witt, Gregory Farquhar, Nantas Nardelli, Tim GJ Rudner, Chia-Man Hung, Philip HS Torr, Jakob Foerster, and Shimon Whiteson · 2019
Cited alongside, same era.
Multi-agent reinforcement learning: Independent vs. cooperative agents
Ming Tan
Cited in the paper.
Multi-agent reinforcement learning: Independent vs. cooperative agents
Ming Tan
Cited in the paper.
Javier Yu, Joseph Vincent, and Mac Schwager · 2022
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