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We explore value-based multi-agent reinforcement learning (MARL) in the popular paradigm of centralized training with decentralized execution (CTDE).
Influence-based multi-agent exploration
Tonghan Wang, Jianhao Wang, Yi Wu, and Chongjie Zhang · 1910
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Learning nearly decomposable value functions via communication minimization
Tonghan Wang, Jianhao Wang, Chongyi Zheng, and Chongjie Zhang · 1910
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Planning, learning and coordination in multiagent decision processes
Craig Boutilier · 1996
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Approximation with artificial neural networks
Balázs Csanád Csáji et al · 2001
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Multi-agent reinforcement learning with emergent roles
Tonghan Wang, Heng Dong, Victor Lesser, and Chongjie Zhang · 2003
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Towards understanding linear value decomposition in cooperative multi-agent q-learning
Jianhao Wang, Zhizhou Ren, Beining Han, and Chongjie Zhang · 2006
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Off-policy multi-agent decomposed policy gradients
Yihan Wang, Beining Han, Tonghan Wang, Heng Dong, and Chongjie Zhang · 2007
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Optimal and approximate q-value functions for decentralized pomdps
Frans A Oliehoek, Matthijs TJ Spaan, and Nikos Vlassis · 2008
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Rode: Learning roles to decompose multi-agent tasks
Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, and Chongjie Zhang · 2010
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Coordinated multi-agent reinforcement learning in networked distributed pomdps
Chongjie Zhang and Victor Lesser · 2011
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An overview of recent progress in the study of distributed multi-agent coordination
Yongcan Cao, Wenwu Yu, Wei Ren, and Guanrong Chen · 2012
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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The arcade learning environment: An evaluation platform for general agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Multi-agent reinforcement learning as a rehearsal for decentralized planning
Landon Kraemer and Bikramjit Banerjee · 2016
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A concise introduction to decentralized POMDPs , volume 1
Frans A Oliehoek, Christopher Amato, et al · 2016
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Dueling network architectures for deep reinforcement learning
Ziyu Wang, Tom Schaul, Matteo Hessel, Hado Hasselt, Marc Lanctot, and Nando Freitas · 2016
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Off-policy deep reinforcement learning without exploration
Scott Fujimoto, David Meger, and Doina Precup · 2019
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Maven: Multi-agent variational exploration
Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, and Shimon Whiteson · 2019
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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
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Qtran: Learning to factorize with transformation for cooperative multi-agent reinforcement learning
Kyunghwan Son, Daewoo Kim, Wan Ju Kang, David Earl Hostallero, and Yung Yi · 2019
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An optimistic perspective on offline reinforcement learning
Rishabh Agarwal, Dale Schuurmans, and Mohammad Norouzi · 2020
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Maximilian Hüttenrauch, Adrian Šošić, and Gerhard Neumann · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Qmix: Monotonic value function factorisation for deep multi-agent reinforcement learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder Witt, Gregory Farquhar, Jakob Foerster, and Shimon Whiteson · 2018
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Value-decomposition networks for cooperative multi-agent learning based on team reward
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinicius Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z Leibo, Karl Tuyls, et al · 2018
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Challenges of real-world reinforcement learning
Gabriel Dulac-Arnold, Daniel Mankowitz, and Todd Hester · 2019
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Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, and Sergey Levine · 2020
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Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu · 2020
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Weighted qmix: Expanding monotonic value function factorisation for deep multi-agent reinforcement learning
Tabish Rashid, Gregory Farquhar, Bei Peng, and Shimon Whiteson · 2020
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Qatten: A general framework for cooperative multiagent reinforcement learning
Yaodong Yang, Jianye Hao, Ben Liao, Kun Shao, Guangyong Chen, Wulong Liu, and Hongyao Tang · 2020
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Mopo: Model-based offline policy optimization
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