188 citations · 880 across the 70 of their papers we have counts for
4 papers · 1 filter
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
Batuhan Yardim, Semih Cayci, Matthieu Geist +1
Mean-field games have been used as a theoretical tool to obtain an approximate Nash equilibrium for symmetric and anonymous -player games. However, limiting applicability, exist…
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, $…
On the Convergence of Model Free Learning in Mean Field Games
Romuald Elie, Julien Pérolat, Mathieu Laurière +2
Learning by experience in Multi-Agent Systems (MAS) is a difficult and exciting task, due to the lack of stationarity of the environment, whose dynamics evolves as the population l…
Difference of Convex Functions Programming Applied to Control with Expert Data
Bilal Piot, Matthieu Geist, Olivier Pietquin
This paper reports applications of Difference of Convex functions (DC) programming to Learning from Demonstrations (LfD) and Reinforcement Learning (RL) with expert data. This is m…