Sarah Perrin
Sarah Perrin
PhD student, INRIA / CNRS / Univ. Lille
Verified email at - Homepage
Cited by
Cited by
Fictitious play for mean field games: Continuous time analysis and applications
S Perrin, J Pérolat, M Laurière, M Geist, R Elie, O Pietquin
NeurIPS 2020, 2020
Machine learning optimization algorithms & portfolio allocation
S Perrin, T Roncalli
Machine Learning for Asset Management: New Developments and Financial …, 2020
Concave Utility Reinforcement Learning: the Mean-field Game viewpoint
M Geist, J Pérolat, M Laurière, R Elie, S Perrin, O Bachem, R Munos, ...
AAMAS 2022, 2021
Scaling up Mean Field Games with Online Mirror Descent
J Perolat, S Perrin, R Elie, M Laurière, G Piliouras, M Geist, K Tuyls, ...
AAMAS 2022, 2021
Mean Field Games Flock! The Reinforcement Learning Way
S Perrin, M Laurière, J Pérolat, M Geist, R Élie, O Pietquin
IJCAI 2021, 2021
Generalization in Mean Field Games by Learning Master Policies
S Perrin, M Laurière, J Pérolat, R Élie, M Geist, O Pietquin
AAAI 2022, 2021
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
M Laurière, S Perrin, S Girgin, P Muller, A Jain, T Cabannes, G Piliouras, ...
ICML 2022, 2022
Learning Mean Field Games: A Survey
M Laurière, S Perrin, M Geist, O Pietquin
arXiv preprint arXiv:2205.12944, 2022
Solving N-player dynamic routing games with congestion: a mean field approach
T Cabannes, M Lauriere, J Perolat, R Marinier, S Girgin, S Perrin, ...
arXiv preprint arXiv:2110.11943, 2021
Solving N player dynamic routing games with congestion: a mean field approach
A Bayen, E Goubault, J Perolat, ML Lauriere, O Pietquin, R Marinier, ...
Learning algorithms for Mean Field Games
R Elie, M Geist, M Laurière, J Pérolat, S Perrin, O Pietquin, G Pilliouras, ...
PGMO DAYS 2021, 42, 2021
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