Geng Yini, Hu Kaipeng, Shen Chen, Shi Lei, Wang Zhen
School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China.
School of Mechanical Engineering and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an 710072, China.
Chaos. 2019 Aug;29(8):083114. doi: 10.1063/1.5093014.
How to couple different networks is a key issue in interdependent networks, where information sharing and payoff coupling are two frequently used methods. Unlike previous studies, in this paper, we propose a new coupling mode and test its performance in interdependent networks. Specifically, a player tends to seek additional support on another network only if his environment (defined as the proportion of holding different strategies in the neighborhood) is worse enough and exceeds an aspiration level. Conversely, it turns to the traditional version on single network if his environment is pleasing enough (the value of environment is small). Whether to establish additional support will directly influence the range of selecting fittest learning objects. As we can see from numerical results, moderate aspiration introduces diversity into the system and cooperation evolves with the support of network coupling. Besides, we also demonstrate that players with external links on the boundary of cooperative clusters protect internal cooperators and attract more players to cooperate under preferential selection rule.
如何耦合不同网络是相互依存网络中的一个关键问题,其中信息共享和收益耦合是两种常用方法。与以往研究不同,本文提出了一种新的耦合模式,并在相互依存网络中测试其性能。具体而言,只有当参与者的环境(定义为其邻域中持有不同策略的比例)足够差且超过期望水平时,他才倾向于在另一个网络上寻求额外支持。相反,如果他的环境足够好(环境值较小),则转向单网络的传统版本。是否建立额外支持将直接影响最适合学习对象的选择范围。从数值结果可以看出,适度的期望为系统引入了多样性,并且合作在网络耦合的支持下得以发展。此外,我们还证明,在合作集群边界上具有外部链接的参与者能够保护内部合作者,并在优先选择规则下吸引更多参与者进行合作。