61 citations · 333 across the 51 of their papers we have counts for
6 papers · 1 filter
Learning Correlated Equilibria in Mean-Field Games
Paul Muller, Romuald Elie, Mark Rowland +7
The designs of many large-scale systems today, from traffic routing environments to smart grids, rely on game-theoretic equilibrium concepts. However, as the size of an -player…
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…
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…
Reinforcement Learning Algorithm for Mixed Mean Field Control Games
Andrea Angiuli, Nils Detering, Jean-Pierre Fouque +2
We present a new combined \textit{mean field control game} (MFCG) problem which can be interpreted as a competitive game between collaborating groups and its solution as a Nash equ…
Machine Learning architectures for price formation models
Diogo Gomes, Julián Gutiérrez, Mathieu Laurière
Here, we study machine learning (ML) architectures to solve a mean-field games (MFGs) system arising in price formation models. We formulate a training process that relies on a min…
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
Mathieu Laurière, Sarah Perrin, Sertan Girgin +8
Mean Field Games (MFGs) have been introduced to efficiently approximate games with very large populations of strategic agents. Recently, the question of learning equilibria in MFGs…