3 citations · 9 across the 5 of their papers we have counts for
5 papers · 1 filter
Multi-population Mean Field Games with Multiple Major Players: Application to Carbon Emission Regulations
Gokce Dayanikli, Mathieu Lauriere
In this paper, we propose and study a mean field game model with multiple populations of minor players and multiple major players, motivated by applications to the regulation of ca…
Machine Learning architectures for price formation models with common noise
Diogo Gomes, Julian Gutierrez, Mathieu Laurière
We propose a machine learning method to solve a mean-field game price formation model with common noise. This involves determining the price of a commodity traded among rational ag…
The communication complexity of functions with large outputs
Lila Fontes, Sophie Laplante, Mathieu Lauriere +1
We study the two-party communication complexity of functions with large outputs, and show that the communication complexity can greatly vary depending on what output model is consi…
Actor-Critic learning for mean-field control in continuous time
Noufel Frikha, Maximilien Germain, Mathieu Laurière +2
We study policy gradient for mean-field control in continuous time in a reinforcement learning setting. By considering randomised policies with entropy regularisation, we derive a…
Deep Learning for Mean Field Optimal Transport
Sebastian Baudelet, Brieuc Frénais, Mathieu Laurière +2
Mean field control (MFC) problems have been introduced to study social optima in very large populations of strategic agents. The main idea is to consider an infinite population and…