3 papers
math.OC2025
Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods
René Carmona, Mathieu Laurière, Zongjun Tan
We investigate reinforcement learning in the setting of Markov decision processes for a large number of exchangeable agents interacting in a mean field manner. Applications include…
cs.LG2024
Learning in Mean Field Games: A Survey
Mathieu Laurière, Sarah Perrin, Julien Pérolat +5
Non-cooperative and cooperative games with a very large number of players have many applications but remain generally intractable when the number of players increases. Introduced b…
math.OC2024
A Machine Learning Method for Stackelberg Mean Field Games
Gokce Dayanikli, Mathieu Lauriere
We propose a single-level numerical approach to solve Stackelberg mean field game (MFG) problems. In Stackelberg MFG, an infinite population of agents play a non-cooperative game a…