The Ultimatum Game in complex networks

被引:72
|
作者
Sinatra, R. [1 ,2 ,3 ]
Iranzo, J. [4 ,5 ]
Gomez-Gardenes, J. [1 ,5 ,6 ]
Floria, L. M. [5 ,7 ]
Latora, V. [1 ,2 ,3 ]
Moreno, Y. [8 ]
机构
[1] Scuola Super Catania, Lab Sistemi Complessi, I-95123 Catania, Italy
[2] Catania Univ, Dipartimento Fis & Astron, I-95123 Catania, Italy
[3] Ist Nazl Fis Nucl, I-95123 Catania, Italy
[4] Ctr Astrobiol CSIC INTA, Madrid 28850, Spain
[5] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst BIFI, E-50009 Zaragoza, Spain
[6] Univ Rey Juan Carlos, ESCET, Dept Matemat Aplicada, Madrid 28933, Spain
[7] Univ Zaragoza, Dept Fis Mat Condensada, E-50009 Zaragoza, Spain
[8] Univ Zaragoza, Dept Theoret Phys, E-50009 Zaragoza, Spain
关键词
network dynamics; applications to game theory and mathematical economics; socio-economic networks; ALTRUISTIC PUNISHMENT; COOPERATION; EVOLUTION; BEHAVIOR; MODEL;
D O I
10.1088/1742-5468/2009/09/P09012
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
We address the problem of how cooperative (altruistic-like) behavior arises in natural and social systems by analyzing an Ultimatum Game in complex networks. Specifically, players of three types are considered: (a) empathetic, whose aspiration levels, and offers, are equal, (b) pragmatic, who do not distinguish between the different roles and aim to obtain the same benefit, and (c) agents whose aspiration levels, and offers, are independent. We analyze the asymptotic behavior of pure populations with different topologies using two kinds of strategic update rules: natural selection, which relies on replicator dynamics, and social penalty, inspired by the Bak-Sneppen dynamics, in which players are subject to a social selection rule penalizing not only the less fit individuals, butalso their first neighbors. We discuss the emergence of fairness in the different settings and network topologies.
引用
收藏
页数:22
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