Perolat, Julien

25 publications

TMLR 2023 Population-Based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas Anthony, Julien Perolat

AAAI 2022 Generalization in Mean Field Games by Learning Master Policies Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin

ICML 2022 Scalable Deep Reinforcement Learning Algorithms for Mean Field Games Mathieu Lauriere, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Perolat, Romuald Elie, Olivier Pietquin, Matthieu Geist

JAIR 2021 Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning Justin Fu, Andrea Tacchetti, Julien Pérolat, Yoram Bachrach

ICML 2021 From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls

JAIR 2021 Game Plan: What AI Can Do for Football, and What Football Can Do for AI 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

IJCAI 2021 Mean Field Games Flock! the Reinforcement Learning Way Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin

ICLR 2020 A Generalized Training Approach for Multiagent Learning Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Perolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Remi Munos

ICML 2020 Fast Computation of Nash Equilibria in Imperfect Information Games Remi Munos, Julien Perolat, 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

NeurIPS 2020 Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications Sarah Perrin, Julien Perolat, Mathieu Lauriere, Matthieu Geist, Romuald Elie, Olivier Pietquin

ACML 2020 Foolproof Cooperative Learning Alexis Jacq, Julien Perolat, Matthieu Geist, Olivier Pietquin

NeurIPS 2020 Learning to Play No-Press Diplomacy with Best Response Policy Iteration Thomas Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas Hudson, Nicolas Porcel, Marc Lanctot, Julien Perolat, Richard Everett, Satinder P. Singh, Thore Graepel, Yoram Bachrach

AAAI 2020 On the Convergence of Model Free Learning in Mean Field Games Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin

IJCAI 2019 Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls

NeurIPS 2019 Multiagent Evaluation Under Incomplete Information Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Perolat, Michal Valko, Georgios Piliouras, Remi Munos

ICML 2019 Open-Ended Learning in Symmetric Zero-Sum Games David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech Czarnecki, Julien Perolat, Max Jaderberg, Thore Graepel

AISTATS 2018 Actor-Critic Fictitious Play in Simultaneous Move Multistage Games Julien Pérolat, Bilal Piot, Olivier Pietquin

NeurIPS 2018 Actor-Critic Policy Optimization in Partially Observable Multiagent Environments Sriram Srinivasan, Marc Lanctot, Vinicius Zambaldi, Julien Perolat, Karl Tuyls, Remi Munos, Michael Bowling

NeurIPS 2018 Re-Evaluating Evaluation David Balduzzi, Karl Tuyls, Julien Perolat, Thore Graepel

NeurIPS 2017 A Multi-Agent Reinforcement Learning Model of Common-Pool Resource Appropriation Julien Pérolat, Joel Z. Leibo, Vinicius Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel

NeurIPS 2017 A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning Marc Lanctot, Vinicius Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Perolat, David Silver, Thore Graepel

AISTATS 2017 Learning Nash Equilibrium for General-Sum Markov Games from Batch Data Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin

AISTATS 2016 On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games Julien Pérolat, Bilal Piot, Bruno Scherrer, Olivier Pietquin

ICML 2016 Softened Approximate Policy Iteration for Markov Games Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin

ICML 2015 Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games Julien Perolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin