Anahtarcı, BerkayKarıksız, Can DehaSaldı, Naci2022-08-082022-08-0820210743-1546http://hdl.handle.net/10679/7777https://doi.org/10.1109/CDC45484.2021.9682954In this paper, we consider learning of discrete-time mean-field games under an average cost criterion. We propose a Q-iteration algorithm via Banach Fixed Point Theorem to compute the mean-field equilibrium when the model is known. We then extend this algorithm to the learning setting by using fitted Q-iteration and establish the probabilistic convergence of the proposed learning algorithm. Our work on learning in average-cost mean-field games appears to be the first in the literature.engrestrictedAccessconferenceObject2021-December3048305300078199030211510.1109/CDC45484.2021.96829542-s2.0-85126035903