Social network learning: Uncertainty, heterogeneity, and the application in principal–agent relationships

This paper employs algebraic transformation to describe complex social network learning (SNL) behaviors under continuous expected payoff. Three distinct algorithms are then introduced that factor in uncertainty and heterogeneity. We find that individuals' strategies tend to converge through SNL...

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Veröffentlicht in:	Mathematical methods in the applied sciences 2024-04, Vol.47 (6), p.4697-4733
Hauptverfasser:	Hong, Yilin, Ding, Chuan, Liu, Peng
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms consensus reaching Convergence Heterogeneity Network topologies network topology principal–agent social network Social networks Uncertainty
Online-Zugang:	Volltext
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