In this paper we present an overview of the field of deterministic approximation of Markov
processes, both in discrete and continuous times. We will discuss mean field approximation …

This review presents and reviews various solved and open problems in develo**,
analyzing, and mitigating epidemic spreading processes under human decision-making. We …

Written by leading experts in the field, Game Theory and Learning for Wireless Networks
Covers how theory can be used to solve prevalent problems in wireless networks such as …

We study a class of linear-quadratic-Gaussian (LQG) control problems with N decision
makers, where the basic objective is to minimize a social cost as the sum of N individual …

In this paper, we study a class of risk-sensitive mean-field stochastic differential games. We
show that under appropriate regularity conditions, the mean-field value of the stochastic …

In this paper we study stochastic dynamic games with many players; these are a
fundamental model for a wide range of economic applications. The standard solution …

We study learning in a dynamic setting where identical copies of a good are sold over time
through a sequence of second-price auctions. Each agent in the market has an unknown …

A mean-field-type game is a game in which the instantaneous payoffs and/or the state
dynamics functions involve not only the state and the action profile but also the joint …

The purpose of this paper is to understand phase transition in noncooperative dynamic
games with a large number of agents. Applications are found in neuroscience, biology, and …

Although valued for its ability to allow teams to collaborate and foster coalitional behaviors
among the participants, game theory's application to networking systems is not without …