Learning in discrete-time average-cost mean-field games

Name: Learning in discrete-time average-cost mean-field games
Author: Anahtarcı, Berkay, Karıksız, Can Deha, Saldı, Naci

İsim	Learning in discrete-time average-cost mean-field games
Yazar	Anahtarcı, Berkay, Karıksız, Can Deha, Saldı, Naci
Basım Tarihi:	2021
Basım Yeri	- IEEE
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0743-1546
Kayıt Numarası	347267a5-42f6-44f1-9f2d-9cd7ee650c03
Lokasyon	Natural and Mathematical Sciences
Tarih	2021
Örnek Metin	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

Kaynağa git Özyeğin Üniversitesi

Aramaya Dön

Özyeğin Üniversitesi

Kaynağa git

Learning in discrete-time average-cost mean-field games

Yazar Anahtarcı, Berkay, Karıksız, Can Deha, Saldı, Naci

Basım Tarihi 2021

Basım Yeri - IEEE

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0743-1546

Kayıt Numarası 347267a5-42f6-44f1-9f2d-9cd7ee650c03

Lokasyon Natural and Mathematical Sciences

Tarih 2021

Örnek Metin 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