过程(计算)
计算机科学
群体智能
社会学习
社会智力
人工智能
反事实条件
钥匙(锁)
社会福利
群体行为
社会知识
机器学习
认知心理学
心理学
社会心理学
知识管理
计算机安全
社会学
政治学
反事实思维
粒子群优化
社会科学
操作系统
法学
作者
Peng Lü,Feier Wen,Yan Li,Dianhan Chen
标识
DOI:10.1016/j.eswa.2022.117878
摘要
It is hard for individuals to handle social common risk, such as terrorism attacks (mass shooting). However, it can be contained, if they can be organized and behave intelligently. To obtain this swarm intelligence pattern, social knowledge should be captured to guide behaviors of isolated individuals. Here, we explore how swarm intelligence can be achieved by individual behaviors during social learning process. We have solved two issues. The first is to obtain social knowledge. Based on agent-based model of real target case, we calculate the optimal solution based on which we infer outcomes of all possible situations. Then, the matrix of social knowledge can be formed; The second is social learning process of individuals. Guided by the social knowledge, they all know that others will be mobilized as well. The key information is the minimal valid size of heroes, and all social members know that this condition is not difficult to satisfy. Thus, more individuals will be mobilized and become the Heroes to fight bravely against the shooter(s). Comparing two patterns, we obtain precise outcomes of how social losses (civilian deaths and injuries) can be reduced. Therefore, guided by clear social knowledge, social welfare can be enhanced substantially.
科研通智能强力驱动
Strongly Powered by AbleSci AI