Asymmetrical Interactions Driven by Strategic Persistence Effectively Alleviates Social Dilemmas in Spatial Games

作     者：Li, Xiaopeng Wang, Zhonglin Xu, Yan Zhang, Hui Yu, Guihai 

作者机构：College of Big Data Statistics Guizhou University of Finance and Economics Guizhou Guiyang550025 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin300384 China School of Information Guizhou University of Finance and Economics Guizhou Guiyang550025 China Guangxi Key Laboratory of Big Data in Finance and Economics Guangxi University of Finance and Ecomonics Nanning530003 China 

出 版 物：《SSRN》 

年 卷 期：2024年

核心收录：

主　　题：Feedback 

摘      要：Asymmetry is a common phenomenon in real life due to constraints such as status, age, information, reputation, and so on. Yet it is still unclear how asymmetric interactions driven by adaptive feedback affect the evolution of cooperation. To this end, we creatively propose a novel asymmetric interaction model driven by strategy persistence to unravel this mystery. In particular, players whose strategy persistence is beyond the threshold β are the pearls for being able to interact with all of the neighbors. Otherwise, they can only interact with half of their neighbors as the layfolks. As the strategy persistence is always updated, leading to the fact that the pearls and the layfolks maybe switch at any time, which adds uncertainty to the evolution of cooperation. Simulation results show that the asymmetric interaction of adaptive feedback effectively alleviates social dilemmas, thus opening up a path for cooperators to survive. Moreover, with the increase of β, there is an appropriate interval resulting in the optimal evolution of cooperation. Micro analysis further indicates that the pearl cooperators play an irreplaceable pivotal role in promoting the evolution of cooperation. At last, we verify and extend the applicability and robustness of the designed model through other social dilemmas, network topologies, and strategy update patterns © 2024, The Authors. All rights reserved.