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Mean-Field Control (MFC) is a powerful tool to solve Multi-Agent Reinforcement Learning (MARL) problems.
Q-learning
Christopher JCH Watkins and Peter Dayan · 1992
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Ming Tan · 1993
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On-line Q-learning using connectionist systems , volume 37
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Markov decision processes: discrete stochastic dynamic programming
Martin L Puterman · 2014
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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Optimal resource allocation for competitive spreading processes on bilayer networks
Nicholas J Watkins, Cameron Nowzari, Victor M Preciado, and George J Pappas · 2016
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Value-decomposition networks for cooperative multi-agent learning
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinicius Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z Leibo, Karl Tuyls, et al · 2017
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Probabilistic Theory of Mean Field Games with Applications I-II
René Carmona, François Delarue, et al · 2018
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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
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Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, and Mingyi Hong · 2018
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Abubakr O Al-Abbasi, Arnob Ghosh, and Vaneet Aggarwal · 2019
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S Sh Alaviani and Nicola Elia · 2019
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Graphon mean field games and the gmfg equations: ε \varepsilon -nash equilibria
Peter E Caines and Minyi Huang · 2019
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On the theory of policy gradient methods: Optimality, approximation, and distribution shift
Alekh Agarwal, Sham M Kakade, Jason D Lee, and Gaurav Mahajan · 2021
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Kai Cui and Heinz Koeppl · 2021
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Mean-field controls with Q-learning for cooperative MARL: convergence and complexity analysis
Haotian Gu, Xin Guo, Xiaoli Wei, and Renyuan Xu · 2021
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Efficient model-based multi-agent mean-field reinforcement learning
Barna Pasztor, Ilija Bogunovic, and Andreas Krause · 2021
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Sequential decomposition of graphon mean field games
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Unified reinforcement q-learning for mean field game and control problems
Andrea Angiuli, Jean-Pierre Fouque, and Mathieu Laurière · 2022
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On the approximation of cooperative heterogeneous multi-agent reinforcement learning (marl) using mean field control (mfc)
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