Julien Pérolat

22 papers · 2015–2022 · 7 conferences · across top CS/AI conferences

Achievements

+14 more ↓

🌍 Conference Polyglot (7) 🏃 Academic Marathon (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird

🧭 Keyword Pioneer 🐝 Cross-Pollinator (10) 🗺️ Taxonomy Completionist (18) 🤝 Dynamic Duo (11) 👑 Triple Crown 🏆 Grand Slam 🔬 Deep Specialist (13) 🧬 Topic Evolution 🏆 Keyword Champion (7) ⚡ Prolific Year (6) 🗃️ Keyword Collector (80) 🔥 Unstoppable (8) 💎 Century Club (22) 📈 Trend Setter

Conferences

NIPS (7) ICML (6) AISTATS (3) AAAI (2) IJCAI (2) ACML (1) ICLR (1)

Top co-authors

Olivier Pietquin (11) Karl Tuyls (9) Marc Lanctot (7) Matthieu Geist (7) Thore Graepel (6) Bilal Piot (5) Rémi Munos (5) Romuald Elie (5) Mathieu Lauriere (5) Mark Rowland (4)

Keywords

nash equilibrium (11) game theory (10) multi-agent system (8) fictitious play (7) zero-sum game (7) reinforcement learning (5) mean field game (5) multi-agent reinforcement learning (4) markov game (4) deep reinforcement learning (3) imperfect information (2) policy optimization (2) model-free learning (2) neural network (2) policy iteration (2) stochastic game (2) two-player zero-sum game (2) equilibrium learning (1) evaluation methodology (1) policy learning (1)

Papers

Scalable Deep Reinforcement Learning Algorithms for Mean Field Games ICML 2022 Generalization in Mean Field Games by Learning Master Policies AAAI 2022 Mean Field Games Flock! The Reinforcement Learning Way IJCAI 2021 From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization ICML 2021 Learning to Play No-Press Diplomacy with Best Response Policy Iteration NIPS 2020 On the Convergence of Model Free Learning in Mean Field Games AAAI 2020 Fast computation of Nash Equilibria in Imperfect Information Games ICML 2020 Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications NIPS 2020 Foolproof Cooperative Learning ACML 2020 A Generalized Training Approach for Multiagent Learning ICLR 2020 Multiagent Evaluation under Incomplete Information NIPS 2019 Open-ended learning in symmetric zero-sum games ICML 2019 Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent IJCAI 2019 Re-evaluating evaluation NIPS 2018 Actor-Critic Fictitious Play in Simultaneous Move Multistage Games AISTATS 2018 Actor-Critic Policy Optimization in Partially Observable Multiagent Environments NIPS 2018 Learning Nash Equilibrium for General-Sum Markov Games from Batch Data AISTATS 2017 A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning NIPS 2017 A multi-agent reinforcement learning model of common-pool resource appropriation NIPS 2017 Softened Approximate Policy Iteration for Markov Games ICML 2016 On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games AISTATS 2016 Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games ICML 2015