Paul Muller
Paul Muller
PhD Student, Deepmind
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Cited by
Cited by
OpenSpiel: A framework for reinforcement learning in games
M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint arXiv:1908.09453, 2019
A Generalized Training Approach for Multiagent Learning
P Muller, S Omidshafiei, M Rowland, K Tuyls, J Perolat, S Liu, D Hennes, ...
ICLR2020, 2019
Game Plan: What AI can do for Football, and What Football can do for AI
K Tuyls, S Omidshafiei, P Muller, Z Wang, J Connor, D Hennes, I Graham, ...
Journal of Artificial Intelligence Research 71, 41-88, 2021
From motor control to team play in simulated humanoid football
S Liu, G Lever, Z Wang, J Merel, SM Eslami, D Hennes, WM Czarnecki, ...
arXiv preprint arXiv:2105.12196, 2021
Mastering the game of Stratego with model-free multiagent reinforcement learning
J Perolat, B De Vylder, D Hennes, E Tarassov, F Strub, V de Boer, ...
Science 378 (6623), 990-996, 2022
Navigating the landscape of multiplayer games
S Omidshafiei, K Tuyls, WM Czarnecki, FC Santos, M Rowland, J Connor, ...
Nature communications 11 (1), 5603, 2020
Multi-agent training beyond zero-sum with correlated equilibrium meta-solvers
L Marris, P Muller, M Lanctot, K Tuyls, T Graepel
International Conference on Machine Learning, 7480-7491, 2021
From motor control to team play in simulated humanoid football
S Liu, G Lever, Z Wang, J Merel, SMA Eslami, D Hennes, WM Czarnecki, ...
Science Robotics 7 (69), eabo0235, 2022
Scalable deep reinforcement learning algorithms for mean field games
M Laurière, S Perrin, S Girgin, P Muller, A Jain, T Cabannes, G Piliouras, ...
International Conference on Machine Learning, 12078-12095, 2022
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO
P Muller, M Rowland, R Elie, G Piliouras, J Perolat, M Lauriere, R Marinier, ...
arXiv preprint arXiv:2111.08350, 2021
Multiagent off-screen behavior prediction in football
S Omidshafiei, D Hennes, M Garnelo, Z Wang, A Recasens, E Tarassov, ...
Scientific reports 12 (1), 8638, 2022
Learning Correlated Equilibria in Mean-Field Games
P Muller, R Elie, M Rowland, M Lauriere, J Perolat, S Perrin, M Geist, ...
arXiv preprint arXiv:2208.10138, 2022
Controller optimization via reinforcement learning on asset avatar
Z Li, P Muller, P Nirgudkar
US Patent App. 16/878,692, 2020
Time-series imputation of temporally-occluded multiagent trajectories
S Omidshafiei, D Hennes, M Garnelo, E Tarassov, Z Wang, R Elie, ...
arXiv preprint arXiv:2106.04219, 2021
Temporal difference and return optimism in cooperative multi-agent reinforcement learning
M Rowland, S Omidshafiei, D Hennes, W Dabney, A Jaegle, P Muller, ...
AAMAS ALA Workshop, 2021
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
Z Li, M Lanctot, KR McKee, L Marris, I Gemp, D Hennes, P Muller, ...
arXiv preprint arXiv:2302.00797, 2023
Developing, evaluating and scaling learning agents in multi-agent environments
I Gemp, T Anthony, Y Bachrach, A Bhoopchand, K Bullard, J Connor, ...
AI Communications, 1-14, 2022
Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and Negotiation Games
Z Li, M Lanctot, KR McKee, L Marris, I Gemp, D Hennes, K Larson, ...
Proceedings of the 2023 International Conference on Autonomous Agents and …, 2023
Des Méthodes à Population pour l'Apprentissage par Renforcement Multiagent
P Muller
Automated offset well analysis
C Jeong, FJ Gomez, M Ringer, P Bolchover, P Muller
US Patent 11,143,775, 2021
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