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Dynamic Games and Applications
Erschienen in: Dynamic Games and Applications 3/2016

01.09.2016

Robust Mean Field Games

verfasst von: Dario Bauso, Hamidou Tembine, Tamer Başar

Erschienen in: Dynamic Games and Applications | Ausgabe 3/2016

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Abstract

Recently there has been renewed interest in large-scale games in several research disciplines, with diverse application domains as in the smart grid, cloud computing, financial markets, biochemical reaction networks, transportation science, and molecular biology. Prior works have provided rich mathematical foundations and equilibrium concepts but relatively little in terms of robustness in the presence of uncertainties. In this paper, we study mean field games with uncertainty in both states and payoffs. We consider a population of players with individual states driven by a standard Brownian motion and a disturbance term. The contribution is threefold: First, we establish a mean field system for such robust games. Second, we apply the methodology to production of an exhaustible resource. Third, we show that the dimension of the mean field system can be significantly reduced by considering a functional of the first moment of the mean field process.
Vorheriger Artikel A Dijkstra-Type Algorithm for Dynamic Games
Nächster Artikel Elementary Subpaths in Discounted Stochastic Games

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Fußnoten
1
The distance and the norm referred to throughout the paper is the \(L^2\) norm \(\Vert \cdot \Vert _2\). For instance, \(\hbox {dist}(x,A)=\min _{y \in A} \Vert x-y\Vert _2\).
 
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Metadaten
Titel
Robust Mean Field Games
verfasst von
Dario Bauso
Hamidou Tembine
Tamer Başar
Publikationsdatum
01.09.2016
Verlag
Springer US
Erschienen in
Dynamic Games and Applications / Ausgabe 3/2016
Print ISSN: 2153-0785
Elektronische ISSN: 2153-0793
DOI
https://doi.org/10.1007/s13235-015-0160-4

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