Abstract
The combination of complex networks and game theory is one of the most suitable ways to describe the evolutionary laws of various complex systems. In order to explore the evolution of group cooperation in multiple social dilemmas, a model of a group game with a double-layer network is proposed here. Firstly, to simulate a multiplayer game under multiple identities, we combine a double-layer network and public goods game. Secondly, in order to make an individual’s strategy selection process more in line with a practical context, a new strategy learning method that incorporates individual attributes is designed here, referred to as a “public goods game with selection preferences” (PGG-SP), which makes strategic choices that are more humane and diversified. Finally, a co-evolution mechanism for strategies and topologies is introduced based on the double-layer network, which effectively explains the dynamic game process in real life. To verify the role of multiple double-layer networks with a PGG-SP, four types of double-layer networks are applied in this paper. In addition, the corresponding game results are compared between single-layer, double-layer, static, and dynamic networks. Accordingly, the results show that double-layer networks can facilitate cooperation in group games.
Highlights
Complex networks can productively depict different systems in society and nature [1], in which the edges of the network represent the relationships between systems
We propose a model called public goods game with selection preferences” (PGG-SP) to overcome the problem of previous strategy learning methods not considering individual characteristics, in which an individual’s preferred characteristics represent the probability that an individual tends to cooperate in the game
We used the fraction of cooperators f c to represent the effect of cooperation, which refers number of of individuals who choose to cooperate in the refers to tothe theproportion proportionofofthe the number individuals who choose to cooperate innetthe is the number of all individuals and is the number of c number of indiN
Summary
Complex networks can productively depict different systems in society and nature [1], in which the edges of the network represent the relationships between systems. The PGG-SP model can beneficially express the evolution of human strategies in scenarios involving conflicts between collective and personal interests This model can explain the cooperative evolution problems faced by human beings at multiple levels of social life at the same time in terms of the pertinent influences. We propose a model called PGG-SP to overcome the problem of previous strategy learning methods not considering individual characteristics, in which an individual’s preferred characteristics represent the probability that an individual tends to cooperate in the game. This attribute is the result of individual accumulation through the longterm game.
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