Julien Pérolat

ORCID

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 70

Top Venues

Lille University of Science and Technology, France (PHD)

Education History

Lille University of Science and Technology, France

PHD

Publications

Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas Anthony, Julien Pérolat
Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas W. Anthony, Julien Pérolat
Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning. CoRR (2023)
Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Élie, Olivier Pietquin, Matthieu Geist
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. CoRR (2022)
Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. AAMAS (2022)
Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Elie, Olivier Pietquin, Matthieu Geist
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. ICML (2022)
Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
Scaling Mean Field Games by Online Mirror Descent. AAMAS (2022)
Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. AAMAS (2022)
Ian M. 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
Developing, evaluating and scaling learning agents in multi-agent environments. AI Commun. 35 (4) (2022)
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
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. CoRR (2022)
Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Eric Goubault, Romuald Elie
Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. AAMAS (2022)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
Generalization in Mean Field Games by Learning Master Policies. AAAI (2022)
Ian M. Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar 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
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments. CoRR (2022)
Paul Muller, Romuald Elie, Mark Rowland, Mathieu Laurière, Julien Pérolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, Karl Tuyls
Learning Correlated Equilibria in Mean-Field Games. CoRR (2022)
Justin Fu, Andrea Tacchetti, Julien Pérolat, Yoram Bachrach
Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning. J. Artif. Intell. Res. 71 (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
Generalization in Mean Field Games by Learning Master Policies. CoRR (2021)
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
Shaking the foundations: delusions in sequence models for interaction and control. CoRR (2021)
Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. CoRR (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
Mean Field Games Flock! The Reinforcement Learning Way. CoRR (2021)
Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
Scaling up Mean Field Games with Online Mirror Descent. CoRR (2021)
Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Éric Goubault, Romuald Elie
Solving N-player dynamic routing games with congestion: a mean field approach. CoRR (2021)
Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
Concave Utility Reinforcement Learning: the Mean-field Game viewpoint. CoRR (2021)
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
Game Plan: What AI can do for Football, and What Football can do for AI. J. Artif. Intell. Res. 71 (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
Mean Field Games Flock! The Reinforcement Learning Way. IJCAI (2021)
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
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. ICML (2021)
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
The Advantage Regret-Matching Actor-Critic. CoRR (2020)
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
Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. AAMAS (2020)
Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian M. Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. NeurIPS (2020)
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
Fast computation of Nash Equilibria in Imperfect Information Games. ICML (2020)
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
A Generalized Training Approach for Multiagent Learning. ICLR (2020)
Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. CoRR (2020)
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
Game Plan: What AI can do for Football, and What Football can do for AI. CoRR (2020)
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
Navigating the Landscape of Games. CoRR (2020)
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
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. CoRR (2020)
Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian M. Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. CoRR (2020)
Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. NeurIPS (2020)
Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin
Foolproof Cooperative Learning. ACML (2020)
Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
On the Convergence of Model Free Learning in Mean Field Games. AAAI (2020)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Edward Hughes, Richard Everett, Joel Z. Leibo, Csaba Szepesvári, Thore Graepel
Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. 34 (1) (2020)
David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech M. Czarnecki, Julien Pérolat, Max Jaderberg, Thore Graepel
Open-ended Learning in Symmetric Zero-sum Games. CoRR (2019)
Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos
Multiagent Evaluation under Incomplete Information. NeurIPS (2019)
Shayegan Omidshafiei, Christos H. Papadimitriou, Georgios Piliouras, Karl Tuyls, Mark Rowland, Jean-Baptiste Lespiau, Wojciech M. Czarnecki, Marc Lanctot, Julien Pérolat, Rémi Munos
α-Rank: Multi-Agent Evaluation by Evolution. CoRR (2019)
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
Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence. AI Mag. 40 (3) (2019)
Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin
Foolproof Cooperative Learning. CoRR (2019)
Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. CoRR (2019)
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
OpenSpiel: A Framework for Reinforcement Learning in Games. CoRR (2019)
Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
Approximate Fictitious Play for Mean Field Games. CoRR (2019)
Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos
Multiagent Evaluation under Incomplete Information. CoRR (2019)
David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech Czarnecki, Julien Pérolat, Max Jaderberg, Thore Graepel
Open-ended learning in symmetric zero-sum games. ICML (2019)
Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
Malthusian Reinforcement Learning. AAMAS (2019)
Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls
Neural Replicator Dynamics. CoRR (2019)
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
A Generalized Training Approach for Multiagent Learning. CoRR (2019)
Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. IJCAI (2019)
Julien Pérolat, Bilal Piot, Olivier Pietquin
Actor-Critic Fictitious Play in Simultaneous Move Multistage Games. AISTATS (2018)
Julien Pérolat, Mateusz Malinowski, Bilal Piot, Olivier Pietquin
Playing the Game of Universal Adversarial Perturbations. CoRR (2018)
David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel
Re-evaluating evaluation. NeurIPS (2018)
Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. NeurIPS (2018)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
A Generalised Method for Empirical Game Theoretic Analysis. AAMAS (2018)
Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. CoRR (2018)
Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
Malthusian Reinforcement Learning. CoRR (2018)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
A Generalised Method for Empirical Game Theoretic Analysis. CoRR (2018)
David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel
Re-evaluating evaluation. CoRR (2018)
Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. AISTATS (2017)
Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
A multi-agent reinforcement learning model of common-pool resource appropriation. NIPS (2017)
Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
A multi-agent reinforcement learning model of common-pool resource appropriation. CoRR (2017)
Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR (2017)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
Symmetric Decomposition of Asymmetric Games. CoRR (2017)
Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS (2017)
Julien Pérolat, Bilal Piot, Bruno Scherrer, Olivier Pietquin
On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games. AISTATS (2016)
Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin
Softened Approximate Policy Iteration for Markov Games. ICML (2016)
Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. CoRR (2016)
Merwan Barlier, Julien Pérolat, Romain Laroche, Olivier Pietquin
Human-Machine Dialogue as a Stochastic Game. SIGDIAL Conference (2015)
Julien Pérolat, Inés Couso, Kevin Loquin, Olivier Strauss
Generalizing the Wilcoxon rank-sum test for interval data. Int. J. Approx. Reason. 56 (2015)
Julien Pérolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin
Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games. ICML (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Julien Pérolat