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In multi-agent reinforcement learning, the behaviors that agents learn in a single Markov Game (MG) are typically confined to the given agent number.
Multi-agent reinforcement learning: Independent vs. cooperative agents
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Emma Brunskill and Lihong Li · 2013
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Emilio Parisotto, Jimmy Lei Ba, and Ruslan Salakhutdinov · 2015
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Stochastic neural networks for hierarchical reinforcement learning
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Ryan Lowe, Yi I Wu, Aviv Tamar, Jean Harb, OpenAI Pieter Abbeel, and Igor Mordatch · 2017
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Policy optimization provably converges to nash equilibria in zero-sum linear quadratic games
Kaiqing Zhang, Zhuoran Yang, and Tamer Başar · 2019
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Saurabh Kumar, Aviral Kumar, Sergey Levine, and Chelsea Finn · 2020
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Evolutionary population curriculum for scaling multi-agent reinforcement learning
Qian Long, Zihan Zhou, Abhinav Gupta, Fei Fang, Yi Wu†, and Xiaolong Wang† · 2020
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Attention is all you need
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Parameter sharing is surprisingly useful for multi-agent deep reinforcement learning
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