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Mean-field games (MFGs) are limiting models to approximate $N$-player games, with a number of applications.
OpenSpiel: A framework for reinforcement learning in games
Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinicius Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas Anthony, Edward Hughes, Ivo Danihelka, and Jonah Ryan-Davis · 1908
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Large population stochastic dynamic games: closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle
Minyi Huang, Roland P Malhamé, and Peter E Caines · 2006
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Mean field games
Jean-Michel Lasry and Pierre-Louis Lions · 2007
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QuantEcon.py: A high performance, open source Python code library for economics
Thomas J. Sargent, et al · 2013
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Nashpy: A Python library for 2 player games
Vince Knight · 2016
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Markov Nash equilibria in mean-field games with discounted cost
Naci Saldi, Tamer Basar, and Maxim Raginsky · 2018
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Optuna: A next-generation hyperparameter optimization framework
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, and Masanori Koyama · 2019
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Learning mean-field games
Xin Guo, Anran Hu, Renyuan Xu, and Junzi Zhang · 2019
Cited alongside, same era.
An integral control formulation of mean field game based large scale coordination of loads in smart grids
Arman C Kizilkale, Rabih Salhab, and Roland P Malhamé · 2019
Cited alongside, same era.
A mean field game of portfolio trading and its consequences on perceived correlations
Charles-Albert Lehalle and Charafeddine Mouzouni · 2019
Cited alongside, same era.
Efficient iterative linear-quadratic approximations for nonlinear multi-player general-sum differential games
David Fridovich-Keil, Ellis Ratner, Lasse Peters, Anca D Dragan, and Claire J Tomlin · 2020
Cited alongside, same era.
Fictitious play for mean field games: Continuous time analysis and applications
Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, and Olivier Pietquin · 2020
Cited alongside, same era.
Approximately solving mean field games via entropy-regularized deep reinforcement learning
Kai Cui and Heinz Koeppl · 2021
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GMFG-learning: Learning graphon mean-field games
Kai Cui · 2021
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Scaling up mean field games with online mirror descent
Julien Perolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, and Olivier Pietquin · 2021
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Mean field games flock! the reinforcement learning way
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, and Olivier Pietquin · 2021
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A general framework for learning mean-field games
Xin Guo, Anran Hu, Renyuan Xu, and Junzi Zhang · 2023
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Entropic-MFG: Entropic variational mean-field games
Wilson Jallet · 2020
Cited alongside, same era.
Solving N-player dynamic routing games with congestion: a mean field approach
Theophile Cabannes, Mathieu Lauriere, Julien Perolat, Raphael Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M Bayen, Eric Goubault, and Romuald Elie · 2021
Cited alongside, same era.
MF-OMO: An optimization formulation of mean-field games
Xin Guo, Anran Hu, and Junzi Zhang · 2024
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Anran Hu and Junzi Zhang · 2024
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