4 papers · 1 filter
Self-fictitious-play for Potential Monotone Ergodic Mean-field Games
Yupeng Bai, Mathieu Laurière, Zhenjie Ren +1
We investigate long-time learning in ergodic, potential, monotone mean-field games (MFGs) via a self-fictitious-play (SFP) dynamics coupling an optimally controlled diffusion with…
Neural Parameter Calibration for Finite-State Mean Field Games
Anna C. M. Thöni, Grégoire Lambrecht, Gökçe Dayanıklı +3
Mean field games efficiently approximate a very large population of strategic agents. While these games can aid the understanding of complex systems, their deployment in real-world…
Robust -learning for mean-field control under Wasserstein uncertainty in common noise
Mathieu Laurière, Ariel Neufeld, Kyunghyun Park
In this article, we present a robust -learning algorithm for discrete-time mean-field control problems under Wasserstein uncertainty in the common noise law. The algorithm combi…
Population-Aware Imitation Learning in Mean-field Games with Common Noise
Grégoire Lambrecht, Mathieu Laurière
Mean Field Games (MFGs) provide a powerful framework for modeling the collective behavior of large populations of interacting agents. In this paper, we address the problem of Imita…