Learning in Mean Field Games: the Fictitious Play
Optimization and Control
2015-08-03 v2
Abstract
Mean Field Game systems describe equilibrium configurations in differential games with infinitely many infinitesimal interacting agents. We introduce a learning procedure (similar to the Fictitious Play) for these games and show its convergence when the Mean Field Game is potential.
Keywords
Cite
@article{arxiv.1507.06280,
title = {Learning in Mean Field Games: the Fictitious Play},
author = {Pierre Cardaliaguet and Saeed Hadikhanloo},
journal= {arXiv preprint arXiv:1507.06280},
year = {2015}
}