10 citations · 37 across the 13 of their papers we have counts for
18 papers · 1 filter
Performance of a Markovian neural network versus dynamic programming on a fishing control problem
Mathieu Laurière, Gilles Pagès, Olivier Pironneau
Fishing quotas are unpleasant but efficient to control the productivity of a fishing site. A popular model has a stochastic differential equation for the biomass on which a stochas…
Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance
René Carmona, Mathieu Laurière
Financial markets and more generally macro-economic models involve a large number of individuals interacting through variables such as prices resulting from the aggregate behavior…
Reinforcement Learning for Mean Field Games, with Applications to Economics
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Lauriere
Mean field games (MFG) and mean field control problems (MFC) are frameworks to study Nash equilibria or social optima in games with a continuum of agents. These problems can be use…
Finite State Graphon Games with Applications to Epidemics
Alexander Aurell, Rene Carmona, Gokce Dayanikli +1
We consider a game for a continuum of non-identical players evolving on a finite state space. Their heterogeneous interactions are represented by a graphon, which can be viewed as…
Numerical Methods for Mean Field Games and Mean Field Type Control
Mathieu Lauriere
Mean Field Games (MFG) have been introduced to tackle games with a large number of competing players. Considering the limit when the number of players is infinite, Nash equilibria…
Mean Field Models to Regulate Carbon Emissions in Electricity Production
Rene Carmona, Gokce Dayanikli, Mathieu Lauriere
The most serious threat to ecosystems is the global climate change fueled by the uncontrolled increase in carbon emissions. In this project, we use mean field control and mean fiel…