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Utilizing messages from teammates can improve coordination in cooperative Multi-agent Reinforcement Learning (MARL).
Learning communication for multi-agent systems
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Pablo Hernandez-Leal, Bilal Kartal, and Matthew E Taylor · 2019
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Advantage-weighted regression: Simple and scalable off-policy reinforcement learning
Xue Bin Peng, Aviral Kumar, Grace Zhang, and Sergey Levine · 2019
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The starcraft multi-agent challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schröder de Witt, Gregory Farquhar, Nantas Nardelli, Tim GJ Rudner, Chia-Man Hung, Philip HS Torr, Jakob N 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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Behavior regularized offline reinforcement learning
Yifan Wu, George Tucker, and Ofir Nachum · 2019
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Learning to communicate in multi-agent reinforcement learning: A review
Mohamed Salah Zaïem and Etienne Bennequin · 2019
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Efficient communication in multi-agent reinforcement learning via variance based control
Sai Qian Zhang, Qi Zhang, and Jieyu Lin · 2019
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Woojun Kim, Jongeui Park, and Youngchul Sung · 2020
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Conservative Q-learning for offline reinforcement learning
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Conservative Q-learning for offline reinforcement learning
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Benchmarking multi-agent deep reinforcement learning algorithms in cooperative tasks
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Empirical study of off-policy policy evaluation for reinforcement learning
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