Differentially private distributed algorithms for stochastic aggregative games

Designing privacy-preserving distributed algorithms for stochastic aggregative games is urgent due to the privacy issues caused by information exchange between players. This paper proposes two differentially private distributed algorithms seeking the Nash equilibrium in stochastic aggregative games....

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Veröffentlicht in:	Automatica (Oxford) Jg. 142; S. 110440
Hauptverfasser:	Wang, Jimin, Zhang, Ji-Feng, He, Xingkang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.08.2022
Schlagworte:	Differential privacy Distributed algorithms Stochastic aggregative games Stochastic approximation Differential privacy Stochastic approximation Distributed algorithms Stochastic aggregative games
ISSN:	0005-1098, 1873-2836
Online-Zugang:	Volltext
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