Learning in discrete-time average-cost mean-field games
| Title | Learning in discrete-time average-cost mean-field games |
|---|---|
| Author | Anahtarcı, Berkay, Karıksız, Can Deha, Saldı, Naci |
| Publication Date: | 2021 |
| Publication Place | - IEEE |
| Type | Document |
| Language | English |
| Digital | Yes |
| Manuscript | No |
| Library: | Özyeğin University |
| Library Asset ID | 0743-1546 |
| Record ID | 347267a5-42f6-44f1-9f2d-9cd7ee650c03 |
| Library Location | Natural and Mathematical Sciences |
| Date | 2021 |
| Sample Text | In 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. |
| DOI | 10.1109/CDC45484.2021.9682954 |
| Cilt | 2021-December |
