Public goods game on coevolving networks driven by the similarity and difference of payoff. (September 2022)

• Record Type: Journal Article
• Authors: Wang, Chaoqian; Lin, Zongzhe; Rothman, Dale S.
• Is Part Of: Chaos, solitons and fractals. Volume 162(2022)
• Publication Date: 2022-09
• Subjects: Evolutionary game -- Public goods game -- Cooperation -- Complex networks -- Clustering coefficient; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2022.112461
• Languages: English
• ISSNs: 0960-0779

Abstract

Abstract: Humans try to escape from their mundane lives and look for different experiences. Based on this assumption and story, this paper considers asynchronous public goods games on coevolving networks driven by payoff difference. Starting from a regular square lattice, agents disconnect from neighbors who have similar payoff, and they connect to new agents with different payoff. We measure network cohesion by the clustering coefficient. The results demonstrate multiple stages of the system. There are two stages where cooperation sustains. One is convex, and another is concave. When there is a shift from the defective stage to a cooperative one, the system generates a strong network cohesion facilitating cooperation to begin emerging. Near the tipping point of the two cooperative stages, the system strengthens the network cohesion to promote the stage transition. The time-dependent networks weaken the possibility of counteracting defection by forming cooperative alliances, which happens in the classic public goods game. However, the disconnection from similar payoff and the connection to different payoff can be matched appropriately to sustain cooperation best.