An evolutionary game with revengers and sufferers on complex networks

Yuji Zhang, Ziyan Zeng, Bin Pi and Minyu Feng

Applied Mathematics and Computation, 2023, vol. 457, issue C

Abstract: The networked evolutionary game theory makes investigations on how the emergence of cooperative behaviors in the real world possible. Many researches based on costly punishment have found profound achievements. However, the order of punishment and timely update of payoff in the process of punishment do not get much attention. Therefore, based on the above deficiencies, we study a revenge-based prisoner’s dilemma game on square-lattice and small-world networks to explore how it affects the emergence and maintenance of cooperation behaviors on complex networks. In simulations, we exhibit the evolution of the cooperation frequency as the population processes and probe the effects of the loss function, the number of players updating strategies, the cost-to-benefit ratio, and network size on the cooperation frequency, and further demonstrate the evolution of the number of revengers and sufferers over time, which may help to understand the role of them played in networks. By varying corresponding revenge parameters, our proposed mechanism helps to overcome social dilemmas. Moreover, we find the phenomenon that the cooperation frequency declines and then rises in small-world networks under certain conditions, which we validate from the variance of the numbers of revengers and sufferers over time. Our work may help to illuminate the study of evolutionary games with revengers and sufferers.

Keywords: Evolutionary game; Revenge and suffer; Network science; Cooperation (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:457:y:2023:i:c:s0096300323003375

DOI: 10.1016/j.amc.2023.128168

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