title: Unfavorable Individuals in Social Gaming Networks.
abstract: In social gaming networks, the current research focus has been on the origin of widespread reciprocal behaviors when individuals play non-cooperative games. In this paper, we investigate the topological properties of unfavorable individuals in evolutionary games. The unfavorable individuals are defined as the individuals gaining the lowest average payoff in a round of game. Since the average payoff is normally considered as a measure of fitness, the unfavorable individuals are very likely to be eliminated or change their strategy updating rules from a Darwinian perspective. Considering that humans can hardly adopt a unified strategy to play with their neighbors, we propose a divide-and-conquer game model, where individuals can interact with their neighbors in the network with appropriate strategies. We test and compare a series of highly rational strategy updating rules. In the tested scenarios, our analytical and simulation results surprisingly reveal that the less-connected individuals in degree-heterogeneous networks are more likely to become the unfavorable individuals. Our finding suggests that the connectivity of individuals as a social capital fundamentally changes the gaming environment. Our model, therefore, provides a theoretical framework for further understanding the social gaming networks.
authors.affiliation: Department of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
authors.forename: Yichao
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Hong Kong SAR, China.
authors.forename: Guanrong
authors.initials: G
authors.lastname: Chen
authors.affiliation: Department of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
authors.forename: Jihong
authors.initials: J
authors.lastname: Guan
authors.affiliation: Department of Computer Science and Engineering, Fudan University, Shanghai 200433, China.|Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China.
authors.forename: Zhongzhi
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: Department of Computer Science and Engineering, Fudan University, Shanghai 200433, China.|Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China.
authors.forename: Shuigeng
authors.initials: S
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D005716:Game Theory; D006801:Humans; D008962:Models, Theoretical; D060756:Social Networking