Markov--Nash equilibria in mean-field games with discounted cost
In this paper, we consider discrete-time dynamic games of the mean-field type with a finite
number N of agents subject to an infinite-horizon discounted-cost optimality criterion. The …
number N of agents subject to an infinite-horizon discounted-cost optimality criterion. The …
Approximate Markov-Nash equilibria for discrete-time risk-sensitive mean-field games
In this paper, we study a class of discrete-time mean-field games under the infinite-horizon
risk-sensitive optimality criterion. Risk sensitivity is introduced for each agent (player) via an …
risk-sensitive optimality criterion. Risk sensitivity is introduced for each agent (player) via an …
Approximate Nash equilibria in partially observed stochastic games with mean-field interactions
Establishing the existence of Nash equilibria for partially observed stochastic dynamic
games is known to be quite challenging, with the difficulties stemming from the noisy nature …
games is known to be quite challenging, with the difficulties stemming from the noisy nature …
Partially observed discrete-time risk-sensitive mean field games
In this paper, we consider discrete-time partially observed mean-field games with the risk-
sensitive optimality criterion. We introduce risk-sensitivity behavior for each agent via an …
sensitive optimality criterion. We introduce risk-sensitivity behavior for each agent via an …
Stationarity and uniform in time convergence for the graphon particle system
E Bayraktar, R Wu - Stochastic Processes and their Applications, 2022 - Elsevier
We consider the long time behavior of heterogeneously interacting diffusive particle systems
and their large population limit. The interaction is of mean field type with weights …
and their large population limit. The interaction is of mean field type with weights …
Nonlinear Markov processes in big networks
QL Li - Special matrices, 2016 - degruyter.com
Big networks express multiple classes of large-scale networks in many practical areas such
as computer networks, internet of things, cloud computation, manufacturing systems …
as computer networks, internet of things, cloud computation, manufacturing systems …
Discrete-time risk-sensitive mean-field games
N Saldi, T Basar, M Raginsky - arXiv preprint arXiv:1808.03929, 2018 - arxiv.org
In this paper, we study a class of discrete-time mean-field games under the infinite-horizon
risk-sensitive discounted-cost optimality criterion. Risk-sensitivity is introduced for each …
risk-sensitive discounted-cost optimality criterion. Risk-sensitivity is introduced for each …
On Time-Inconsistency in Mean Field Games
E Bayraktar, Z Wang - arXiv preprint arXiv:2312.07770, 2023 - arxiv.org
We investigate an infinite-horizon time-inconsistent mean-field game (MFG) in a discrete
time setting. We first present a classic equilibrium for the MFG and its associated existence …
time setting. We first present a classic equilibrium for the MFG and its associated existence …
Learning agents in Black–Scholes financial markets
Black–Scholes (BS) is a remarkable quotation model for European option pricing in financial
markets. Option prices are calculated using an analytical formula whose main inputs are …
markets. Option prices are calculated using an analytical formula whose main inputs are …
Quantitative evaluation of an active Chemotaxis model in Discrete time
AP Majumder - arXiv preprint arXiv:1701.02064, 2017 - arxiv.org
A system of $ N $ particles in a chemical medium in $\mathbb {R}^{d} $ is studied in a
discrete time setting. Underlying interacting particle system in continuous time can be …
discrete time setting. Underlying interacting particle system in continuous time can be …