61 citations · 333 across the 51 of their papers we have counts for
10 papers · 1 filter
Optimal incentives to mitigate epidemics: a Stackelberg mean field game approach
Alexander Aurell, Rene Carmona, Gokce Dayanikli +1
Motivated by models of epidemic control in large populations, we consider a Stackelberg mean field game model between a principal and a mean field of agents evolving on a finite st…
Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games
René Carmona, Kenza Hamidouche, Mathieu Laurière +1
In this paper, zero-sum mean-field type games (ZSMFTG) with linear dynamics and quadratic utility are studied under infinite-horizon discounted utility function. ZSMFTG are a class…
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
Sarah Perrin, Julien Perolat, Mathieu Laurière +3
In this paper, we deepen the analysis of continuous time Fictitious Play learning algorithm to the consideration of various finite state Mean Field Game settings (finite horizon, $…
Unified Reinforcement Q-Learning for Mean Field Game and Control Problems
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
We present a Reinforcement Learning (RL) algorithm to solve infinite horizon asymptotic Mean Field Game (MFG) and Mean Field Control (MFC) problems. Our approach can be described a…
Learning a functional control for high-frequency finance
Laura Leal, Mathieu Laurière, Charles-Albert Lehalle
We use a deep neural network to generate controllers for optimal trading on high frequency data. For the first time, a neural network learns the mapping between the preferences of…
COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability
Arthur Charpentier, Romuald Elie, Mathieu Laurière +1
We consider here an extended SIR model, including several features of the recent COVID-19 outbreak: in particular the infected and recovered individuals can either be detected (+)…
Convergence of large population games to mean field games with interaction through the controls
Mathieu Laurière, Ludovic Tangpi
This work considers stochastic differential games with a large number of players, whose costs and dynamics interact through the empirical distribution of both their states and thei…
Mean Field Games and Applications: Numerical Aspects
Yves Achdou, Mathieu Laurière
The theory of mean field games aims at studying deterministic or stochastic differential games (Nash equilibria) as the number of agents tends to infinity. Since very few mean fiel…
Connecting GANs, MFGs, and OT
Haoyang Cao, Xin Guo, Mathieu Laurière
Generative adversarial networks (GANs) have enjoyed tremendous success in image generation and processing, and have recently attracted growing interests in financial modelings. Thi…
Large Banking Systems with Default and Recovery: A Mean Field Game Model
Romuald Élie, Tomoyuki Ichiba, Mathieu Laurière
We consider a mean-field model for large banking systems, which takes into account default and recovery of the institutions. Building on models used for groups of interacting neuro…