Doubly effects of information sharing on interdependent network reciprocity

Abstract

Understanding large-scale cooperation among unrelated individuals is one of the greatest challenges of the 21st century. Since human cooperation evolves on social networks, the theoretical framework of multilayer networks is perfectly suited for studying this fascinating aspect of our biology. To that effect, we here study the cooperation in evolutionary games on interdependent networks, such that players in one network layer play the snowdrift game (SDG), and the prisoner's dilemma game (PDG) in the other layer. Importantly, players are able to share information across two layers, which in turn affects their strategy choices. Monte Carlo simulations reveal that the transfer of information about the strategy of the corresponding player in the other network layer alone is enough to significantly promote the overall level of cooperation. However, while the cooperation is markedly enhanced in the layer where the PDG is played, the opposite is true, albeit to a lesser extent, for the layer where the SDG is played. The net increase in cooperation is thus due to a doubly effect of information sharing. We show further that the more complete the information transfer, the more the overall level of cooperation is promoted, and that this holds as long as the information channels between the player do not vary over time. We discuss potential implications of these findings for future human experiments concerning the cooperation on multilayer networks.

Assortativity provides a narrow margin for enhanced cooperation on multilayer networks

“…While the bulk of research concerning evolutionary games on networks has been devoted to single and isolated networks, such as small-world [20][21][22][23][24][25][26], scale-free [27][28][29][30][31][32][33][34][35][36][37][38][39][40][41], coevolving [42][43][44][45][46][47][48][49][50], hierarchical [51,52] and community [53] networks, the focus has in recent years been shifting towards multilayer and interdependent networks [54][55][56][57][58][59][60][61][62][63][64][65][66][67][68]. This research has revealed interdependent network reciproci...…”

The behavioral model and game theory

“…Interactions between psychologists and economists have been marked more by conflict than by collaboration and the absence of a common research language impedes communication between this the disciplines (Manski, 2017). Some of the studies describe the relationship between psychologists and economists (Croson and Miller, 2004;Attanasi and Rosemarie Nagel, 2008;Schotter and Trevin, 2014;De Bruin and Fischhoff, 2017;Xia et al, 2018). In this section, we review and interpret Prisoner's Dilemma with the help of the concept of hyper-rationality.…”

Multi-scale asynchronous belief percolation model on multiplex networks

“…The studies of complex networks have provided many novel ideas and insights for understanding the structure and dynamics of complex systems, such as social ties that link different people and transportation networks that connect different cities [1][2][3][4][5]. In recent years, research efforts have shifted from studying each complex system as a single and isolated network to synthesizing multiple correlated systems as interdependent, multiplex or multilayer networks [6][7][8][9][10][11]. This evolving trend indeed echoes modern technical advancements, such as the Internet of Things, Smart Grid, Ubiquitous Computing, Mobile Web, Big Data and Artificial Intelligence, which contribute a novel perspective that different complex systems often have strong correlations and they can interact with each other through nontrivial means.…”