3 citations · 14 across the 12 of their papers we have counts for
6 papers · 1 filter
How can the tragedy of the commons be prevented?: Introducing Linear Quadratic Mixed Mean Field Games
Gokce Dayanikli, Mathieu Lauriere
In a regular mean field game (MFG), the agents are assumed to be insignificant, they do not realize their effect on the population level and this may result in a phenomenon coined…
A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents
Mathieu Laurière, Ludovic Tangpi, Xuchen Zhou
Graphon games have been introduced to study games with many players who interact through a weighted graph of interaction. By passing to the limit, a game with a continuum of player…
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…
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…
Reinforcement Learning for Intra-and-Inter-Bank Borrowing and Lending Mean Field Control Game
Andrea Angiuli, Nils Detering, Jean-Pierre Fouque +2
We propose a mean field control game model for the intra-and-inter-bank borrowing and lending problem. This framework allows to study the competitive game arising between groups of…