Zombie politics: evolutionary algorithms to counteract the spread of negative opinions

作     者：Hochreiter, Ronald Waldhauser, Christoph 

作者机构：Webster Vienna Private Univ Dept Business & Management Praterstr 23 A-1020 Vienna Austria Raiffeisen Bank Int AG Stadtpk 9 A-1030 Vienna Austria 

出 版 物：《SOFT COMPUTING》 (Soft Comput.)

年 卷 期：2020年第24卷第1期

页      面：591-601页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Dynamic optimization Opinion propagation Epidemiology Evolutionary computing 

摘      要：This paper is about simulating the spread of opinions in a society and about finding ways to counteract that spread. To abstract away from potentially emotionally laden opinions, we instead simulate the spread of a zombie outbreak in a society. The virus causing this outbreak is different from traditional approaches: It not only causes a binary outcome (healthy vs. infected) but rather a continuous outcome. To counteract the outbreak, a discrete number of infection-level-specific treatments are available. This corresponds to acts of mild persuasion or the threats of legal action in the opinion spreading use case. This paper offers a genetic and a cultural algorithm that find the optimal mixture of treatments during the run of the simulation. They are assessed in a number of different scenarios. It is shown that albeit far from being perfect, the cultural algorithm delivers superior performance at lower computational expense.