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Recent advances in multiagent learning have seen the introduction ofa family of algorithms that revolve around the population-based trainingmethod PSRO, showing convergence to Nash, correlated and coarse corre-lated equilibria.
α \alpha -Rank: Multi-Agent Evaluation by Evolution
Shayegan Omidshafiei, Christos Papadimitriou, Georgios Piliouras, Karl Tuyls, Mark Rowland, Jean-Baptiste Lespiau, Wojciech M. Czarnecki, Marc Lanctot, Julien Perolat, and Remi Munos. 2019 · 1903
Earlier work this paper cites.
OpenSpiel: A Framework for Reinforcement Learning in Games
Marc Lanctot et al · 1908
Earlier work this paper cites.
A Review of Cooperative Multi-Agent Deep Reinforcement Learning
Afshin OroojlooyJadid and Davood Hajinezhad. 2021 · 1908
Earlier work this paper cites.
A Generalized Training Approach for Multiagent Learning
Paul Muller et al · 1909
Earlier work this paper cites.
A generalization of Brouwer’s fixed point theorem
Shizuo Kakutani. 1941 · 1941
Earlier work this paper cites.
Iterative solution of games by fictitious play
George W Brown. 1951 · 1951
Earlier work this paper cites.
Minimization by random search techniques
Francisco J Solis and Roger J-B Wets. 1981 · 1981
Earlier work this paper cites.
A General Framework for Learning Mean-Field Games
Xin Guo, Anran Hu, Renyuan Xu, and Junzi Zhang. 2020 · 2003
Earlier work this paper cites.
Correlated equilibria and mean field games: a simple model
Luciano Campi and Markus Fischer. 2021 · 2004
Earlier work this paper cites.
From External to Internal Regret
Avrim Blum and Yishay Mansour. 2005 · 2005
Earlier work this paper cites.
Large population stochastic dynamic games: closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle
Minyi Huang, Roland P Malhamé, Peter E Caines, et al · 2006
Earlier work this paper cites.
Learning, Regret minimization, and Equilibria
A. Blum and Y. Mansour. 2007 · 2007
Earlier work this paper cites.
Computing equilibria in anonymous games. In 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS’07) . IEEE, 83–93
Constantinos Daskalakis and Christos Papadimitriou. 2007 · 2007
Earlier work this paper cites.
Mean Field Games
Jean-Michel Lasry and Pierre-Louis Lions. 2007 · 2007
Cited alongside, same era.
Algorithmic game theory
Noam Nisan, Tim Roughgarden, Eva Tardos, and Vijay V Vazirani. 2007 · 2007
Cited alongside, same era.
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
Sarah Perrin et al · 2007
Cited alongside, same era.
Discretized multinomial distributions and Nash equilibria in anonymous games. In 2008 49th Annual IEEE Symposium on Foundations of Computer Science . IEEE, 25–34
Constantinos Daskalakis and Christos H Papadimitriou. 2008 · 2008
Cited alongside, same era.
Independent reinforcement learners in cooperative markov games: a survey regarding coordination problems
Laetitia Matignon, Guillaume J Laurent, and Nadine Le Fort-Piat. 2012 · 2012
Cited alongside, same era.
Correlated equilibria in static mean-field games
Laura Degl’Innocenti. 2018 · 2018
Later among the works it cites.
A Tutorial on Bayesian Optimization
Peter I. Frazier. 2018 · 2018
Later among the works it cites.
Finite mean field games: fictitious play and convergence to a first order continuous mean field game
Saeed Hadikhanloo and Francisco José Silva. 2018 · 2018
Later among the works it cites.
Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients
Arbaaz Khan, Clark Zhang, Daniel D. Lee, Vijay Kumar, and Alejandro Ribeiro. 2018 · 2018
Later among the works it cites.
Multiagent Evaluation under Incomplete Information. In Advances in Neural Information Processing Systems , H. Wallach, H. Larochelle, A. Beygelzimer, F. d’Alché Buc, E. Fox, and R. Garnett (Eds.), Vol. 32. Curran Associates, Inc
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Simple adaptive strategies: from regret-matching to uncoupled dynamics . Vol. 4
Sergiu Hart and Andreu Mas-Colell. 2013 · 2013
Cited alongside, same era.
Solving Large Imperfect Information Games Using CFR+
Oskari Tammelin. 2014 · 2014
Cited alongside, same era.
Finding Any Nontrivial Coarse Correlated Equilibrium Is Hard
Siddharth Barman and Katrina Ligett. 2015 · 2015
Cited alongside, same era.
Learning in Mean Field Games: the Fictitious Play
Pierre Cardaliaguet and Saeed Hadikhanloo. 2015 · 2015
Cited alongside, same era.
The CMA Evolution Strategy: A Tutorial
Nikolaus Hansen. 2016 · 2016
Cited alongside, same era.
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
Marc Lanctot et al · 2017
Cited alongside, same era.
Limits and limitations of no-regret learning in games
Barnabé Monnot and Georgios Piliouras. 2017 · 2017
Cited alongside, same era.
Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Perolat, Michal Valko, Georgios Piliouras, and Remi Munos. 2019 · 2019
Later among the works it cites.
Q-learning in regularized mean-field games. In arXiv
Berkay Anahtarci, Can Deha Kariksiz, and Naci Saldi. 2020 · 2020
Later among the works it cites.
On the convergence of model free learning in mean field games. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 34. 7143–7150
Romuald Elie, Julien Perolat, Mathieu Laurière, Matthieu Geist, and Olivier Pietquin. 2020 · 2020
Later among the works it cites.
Entropy based Independent Learning in Anonymous Multi-Agent Settings
Tanvi Verma, Pradeep Varakantham, and Hoong Chuin Lau. 2020 · 2020
Later among the works it cites.
Provable fictitious play for general mean-field games
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, and Andreea Minca. 2020 · 2020
Later among the works it cites.
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
Luke Marris, Paul Muller, et al · 2021
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Scaling up Mean Field Games with Online Mirror Descent
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Learning Correlated Equilibria in Mean-Field Games
Paul Muller, Romuald Elie, Mark Rowland, Mathieu Lauriere, Julien Perolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, and Karl Tuyls. 2022 · 2022
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