1. Investigating the co-evolution of node reputation and edge-strategy in prisoner's dilemma game.
- Author
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Zhu, Peican, Wang, Xiaoyu, Jia, Danyang, Guo, Yangming, Li, Shudong, and Chu, Chen
- Subjects
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PRISONER'S dilemma game , *COEVOLUTION , *DELINQUENT behavior , *REPUTATION - Abstract
• a mechanism is proposed aiming to investigate the co-evolution of personal reputation and strategy under a general framework of interactive diversity. • Numerous simulations are conducted with sufficient analyses of the obtained results being followed. • The consideration of interaction diversity is able to ensure the maintenance of cooperation even if the temptation of adopting antisocial behavior (here, defection is considered) is relatively large. • Various discussions are performed in order to explain the reason of this effect from various perspectives, for instance, by counting the number of various chains and the evolution of clusters. In practice, there exists numerous examples indicating the phenomenon that individuals are inclined to employ different strategies when interacting with the others. This is incurred by the fact that individuals are able to adjust their strategies adaptively under different interacting environments. Scholars have devoted their efforts to this topic; nevertheless, the impact of diverse interactions on cooperation still needs to be further explored. In this manuscript, we propose a mechanism aiming to investigate the co-evolution of personal reputation and strategy under a general framework of interactive diversity (being referred to as edge-strategy for simplicity). Numerous simulations are conducted with sufficient analyses of the obtained results being provided. As illustrated by the evolutionary dynamics, we find that there exists an optimal reputation value which can promote the frequency of cooperation by a large extent. Furthermore, we can clearly conclude that the consideration of interaction diversity is able to ensure the maintenance of cooperation even if the temptation to adopt antisocial behavior is relatively large. Aiming to understand the phenomenon better, we also quantitatively analyze the results by investigating the statistics of interaction chain, cluster size and other microscopic information. Overall, we hope the findings here can provide some interesting insights in solving social dilemmas. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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