Julien Pérolat

74 papers A* 16A 10C 1Journal 43Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning. CoRR Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas W. Anthony, Julien Pérolat
2023	J	`jnl`	Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning. Trans. Mach. Learn. Res. Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas Anthony, Julien Pérolat
2022	A	`conf`	Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. AAMAS Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
2022	J	`jnl`	Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments. CoRR Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls
2022	J	`jnl`	Developing, evaluating and scaling learning agents in multi-agent environments. AI Commun. Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls
2022	A*	`conf`	Generalization in Mean Field Games by Learning Master Policies. AAAI Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
2022	J	`jnl`	Learning Correlated Equilibria in Mean-Field Games. CoRR Paul Muller, Romuald Elie, Mark Rowland, Mathieu Laurière, Julien Pérolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, Karl Tuyls
2022	A	`conf`	Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. AAMAS Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
2022	J	`jnl`	Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. CoRR Julien Pérolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T. Connor, Neil Burch, Thomas W. Anthony, Stephen McAleer, Romuald Elie, Sarah H. Cen, Zhe Wang, Audrunas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen, Tom Eccles, Mark Rowland, Marc Lanctot, Jean-Baptiste Lespiau, Bilal Piot, Shayegan Omidshafiei, Edward Lockhart, Laurent Sifre, Nathalie Beauguerlange, Rémi Munos, David Silver, Satinder Singh, Demis Hassabis, Karl Tuyls
2022	A*	`conf`	Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. ICML Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Elie, Olivier Pietquin, Matthieu Geist
2022	J	`jnl`	Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. CoRR Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Élie, Olivier Pietquin, Matthieu Geist
2022	A	`conf`	Scaling Mean Field Games by Online Mirror Descent. AAMAS Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
2022	A	`conf`	Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. AAMAS Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Eric Goubault, Romuald Elie
2021	J	`jnl`	Concave Utility Reinforcement Learning: the Mean-field Game viewpoint. CoRR Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
2021	J	`jnl`	Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning. J. Artif. Intell. Res. Justin Fu, Andrea Tacchetti, Julien Pérolat, Yoram Bachrach
2021	A*	`conf`	From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. ICML Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
2021	J	`jnl`	Game Plan: What AI can do for Football, and What Football can do for AI. J. Artif. Intell. Res. Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis
2021	J	`jnl`	Generalization in Mean Field Games by Learning Master Policies. CoRR Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
2021	J	`jnl`	Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. CoRR Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
2021	A*	`conf`	Mean Field Games Flock! The Reinforcement Learning Way. IJCAI Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
2021	J	`jnl`	Mean Field Games Flock! The Reinforcement Learning Way. CoRR Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
2021	J	`jnl`	Scaling up Mean Field Games with Online Mirror Descent. CoRR Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
2021	J	`jnl`	Shaking the foundations: delusions in sequence models for interaction and control. CoRR Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg
2021	J	`jnl`	Solving N-player dynamic routing games with congestion: a mean field approach. CoRR Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Éric Goubault, Romuald Elie
2020	A*	`conf`	A Generalized Training Approach for Multiagent Learning. ICLR Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos
2020	J	`jnl`	Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. Karl Tuyls, Julien Pérolat, Marc Lanctot, Edward Hughes, Richard Everett, Joel Z. Leibo, Csaba Szepesvári, Thore Graepel
2020	A*	`conf`	Fast computation of Nash Equilibria in Imperfect Information Games. ICML Rémi Munos, Julien Pérolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls
2020	A*	`conf`	Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. NeurIPS Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
2020	J	`jnl`	Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. CoRR Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
2020	C	`conf`	Foolproof Cooperative Learning. ACML Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin
2020	J	`jnl`	From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. CoRR Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
2020	J	`jnl`	Game Plan: What AI can do for Football, and What Football can do for AI. CoRR Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis
2020	A*	`conf`	Learning to Play No-Press Diplomacy with Best Response Policy Iteration. NeurIPS Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
2020	J	`jnl`	Learning to Play No-Press Diplomacy with Best Response Policy Iteration. CoRR Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
2020	J	`jnl`	Navigating the Landscape of Games. CoRR Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki, Francisco C. Santos, Mark Rowland, Jerome T. Connor, Daniel Hennes, Paul Muller, Julien Pérolat, Bart De Vylder, Audrunas Gruslys, Rémi Munos
2020	A	`conf`	Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. AAMAS Daniel Hennes, Dustin Morrill, Shayegan Omidshafiei, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Paavo Parmas, Edgar A. Duéñez-Guzmán, Karl Tuyls
2020	A*	`conf`	On the Convergence of Model Free Learning in Mean Field Games. AAAI Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
2020	J	`jnl`	The Advantage Regret-Matching Actor-Critic. CoRR Audrunas Gruslys, Marc Lanctot, Rémi Munos, Finbarr Timbers, Martin Schmid, Julien Pérolat, Dustin Morrill, Vinícius Flores Zambaldi, Jean-Baptiste Lespiau, John Schultz, Mohammad Gheshlaghi Azar, Michael Bowling, Karl Tuyls
2019	J	`jnl`	A Generalized Training Approach for Multiagent Learning. CoRR Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos
2019	J	`jnl`	Approximate Fictitious Play for Mean Field Games. CoRR Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
2019	A*	`conf`	Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. IJCAI Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls
2019	J	`jnl`	Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. CoRR Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls
2019	J	`jnl`	Foolproof Cooperative Learning. CoRR Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin
2019	A	`conf`	Malthusian Reinforcement Learning. AAMAS Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
2019	A*	`conf`	Multiagent Evaluation under Incomplete Information. NeurIPS Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos
2019	J	`jnl`	Multiagent Evaluation under Incomplete Information. CoRR Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos
2019	J	`jnl`	Neural Replicator Dynamics. CoRR Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls
2019	J	`jnl`	Open-ended Learning in Symmetric Zero-sum Games. CoRR David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech M. Czarnecki, Julien Pérolat, Max Jaderberg, Thore Graepel
2019	A*	`conf`	Open-ended learning in symmetric zero-sum games. ICML David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech Czarnecki, Julien Pérolat, Max Jaderberg, Thore Graepel
2019	J	`jnl`	OpenSpiel: A Framework for Reinforcement Learning in Games. CoRR Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores 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 W. Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis
2019	J	`jnl`	Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence. AI Mag. Guy Barash, Mauricio Castillo-Effen, Niyati Chhaya, Peter Clark, Huáscar Espinoza, Eitan Farchi, Christopher W. Geib, Odd Erik Gundersen, Seán Ó hÉigeartaigh, José Hernández-Orallo, Chiori Hori, Xiaowei Huang, Kokil Jaidka, Pavan Kapanipathi, Sarah Keren, Seokhwan Kim, Marc Lanctot, Danny Lange, Julian J. McAuley, David R. Martinez, Marwan Mattar, Mausam, Martin Michalowski, Reuth Mirsky, Roozbeh Mottaghi, Joseph C. Osborn, Julien Pérolat, Martin Schmid, Arash Shaban-Nejad, Onn Shehory, Biplav Srivastava, William W. Streilein, Kartik Talamadupula, Julian Togelius, Koichiro Yoshino, Quanshi Zhang, Imed Zitouni
2019	J	`jnl`	α-Rank: Multi-Agent Evaluation by Evolution. CoRR Shayegan Omidshafiei, Christos H. Papadimitriou, Georgios Piliouras, Karl Tuyls, Mark Rowland, Jean-Baptiste Lespiau, Wojciech M. Czarnecki, Marc Lanctot, Julien Pérolat, Rémi Munos
2018	A	`conf`	A Generalised Method for Empirical Game Theoretic Analysis. AAMAS Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
2018	J	`jnl`	A Generalised Method for Empirical Game Theoretic Analysis. CoRR Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
2018	A	`conf`	Actor-Critic Fictitious Play in Simultaneous Move Multistage Games. AISTATS Julien Pérolat, Bilal Piot, Olivier Pietquin
2018	A*	`conf`	Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. NeurIPS Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling
2018	J	`jnl`	Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. CoRR Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling
2018	J	`jnl`	Malthusian Reinforcement Learning. CoRR Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
2018	J	`jnl`	Playing the Game of Universal Adversarial Perturbations. CoRR Julien Pérolat, Mateusz Malinowski, Bilal Piot, Olivier Pietquin
2018	A*	`conf`	Re-evaluating evaluation. NeurIPS David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel
2018	J	`jnl`	Re-evaluating evaluation. CoRR David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel
2017	—	`conf`	A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
2017	J	`jnl`	A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
2017	—	`conf`	A multi-agent reinforcement learning model of common-pool resource appropriation. NIPS Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
2017	J	`jnl`	A multi-agent reinforcement learning model of common-pool resource appropriation. CoRR Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
2017	A	`conf`	Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. AISTATS Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin
2017	—	`—`	Reinforcement Learning: The Multi-Player Case. (Apprentissage par Renforcement: Le Cas Multijoueur). Julien Pérolat
2017	J	`jnl`	Symmetric Decomposition of Asymmetric Games. CoRR Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
2016	J	`jnl`	Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. CoRR Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin
2016	A	`conf`	On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games. AISTATS Julien Pérolat, Bilal Piot, Bruno Scherrer, Olivier Pietquin
2016	A*	`conf`	Softened Approximate Policy Iteration for Markov Games. ICML Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin
2015	A*	`conf`	Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games. ICML Julien Pérolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin
2015	J	`jnl`	Generalizing the Wilcoxon rank-sum test for interval data. Int. J. Approx. Reason. Julien Pérolat, Inés Couso, Kevin Loquin, Olivier Strauss
2015	—	`conf`	Human-Machine Dialogue as a Stochastic Game. SIGDIAL Conference Merwan Barlier, Julien Pérolat, Romain Laroche, Olivier Pietquin