The Communality of Risk: Differentiating the Logic of Risk Governance Based on Evolutionary Game Theory

被引:0
|
作者
Sun, Xiao [1 ]
Qian, Jun [2 ]
Ying, Yanlin [1 ]
Chai, Yueting [1 ]
Liu, Yi [1 ]
机构
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
来源
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS | 2024年
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Communality; evolutionary game theory; risk resistance;
D O I
10.1109/TCSS.2024.3474095
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Human beings live in a world full of risks, from minor risks such as colds and fevers to major crises such as economic crises and hurricanes. How to cope with these risks is a constant topic in the evolution of humankind. The impact of various characteristics of risk on the risk-resistance outcomes has been well studied, including the probability, intensity and spread of risks. However, as an additional dimension independent of the above main characteristics, risk-resistance solutions that are appropriate to the risk have not received sufficient attention. We abstract this characteristic as the relative cost-effectiveness between collective solution and individual solution in resisting a risk and name it communality. Taking communality and intensity as the two main characteristics of risk, we propose a risk-resistance model and explore the critical impact of risk communality on the outcomes of risk resistance. Using numerical analysis, we map the state transition of the population on a two-dimensional surface consisting of communality and intensity. Simulation experiments validate the results from numerical analysis and reveal four regions in this surface, each of which corresponds to a governance structure endogenous to the population. The complex impact of population-endogenous governance structures on the risk-resistance outcomes reflects the real-world challenges of risk governance. This article suggests that social governors need to implement different logics in the face of risks with different communalities.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] How stakeholders influence MaaS implementation? An analysis based on evolutionary game theory
    Ye, Jianhong
    Zheng, Jiaqi
    TRANSPORT POLICY, 2024, 149 : 198 - 210
  • [32] Energy-aware virtual machine consolidation based on evolutionary game theory
    Liu, Xialin
    Wu, Junsheng
    Chen, Lijun
    Zhang, Lili
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2022, 34 (10)
  • [33] A study of dispatcher's route choice model based on evolutionary game theory
    Uchiyama, Naohiro
    Taniguchi, Eiichi
    SEVENTH INTERNATIONAL CONFERENCE ON CITY LOGISTICS, 2012, 39 : 495 - 509
  • [34] Active Defense Model of Wireless Sensor Networks Based on Evolutionary Game Theory
    Qiu, Yihui
    Chen, Zhide
    Xu, Li
    2010 6TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS NETWORKING AND MOBILE COMPUTING (WICOM), 2010,
  • [35] Evolution mechanism of conflict between pedestrian and vehicle based on evolutionary game theory
    Wei Li-Ying
    Cui Yu-Feng
    Li Dong-Ying
    ACTA PHYSICA SINICA, 2018, 67 (19)
  • [36] Agent-Based Simulation of Stakeholder Behaviour through Evolutionary Game Theory
    Svalestuen, Yngve
    Ozturk, Pinar
    Tidemann, Axel
    Tiller, Rachel
    ARTIFICIAL LIFE AND COMPUTATIONAL INTELLIGENCE, 2015, 8955 : 100 - 111
  • [37] Behavior Simulation of "Chinese Style Road Crossing" Based on Evolutionary Game Theory
    Gou, Juanqiong
    Cai, Xiahui
    Dou, Shuihai
    2016 INTERNATIONAL CONFERENCE ON LOGISTICS, INFORMATICS AND SERVICE SCIENCES (LISS' 2016), 2016,
  • [38] Computer virus propagation model based on bounded rationality evolutionary game theory
    Jin, Cong
    Jin, Shu-Wei
    Tan, Hua-Yong
    SECURITY AND COMMUNICATION NETWORKS, 2013, 6 (02) : 210 - 218
  • [39] A Multi-Vehicle Cooperative Routing Method Based on Evolutionary Game Theory
    Lu, Jiawei
    Li, Jinglin
    Yuan, Quan
    Chen, Bo
    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 987 - 994
  • [40] A generic approach for network defense strategies generation based on evolutionary game theory
    Liu, Liang
    Tang, Chuhao
    Zhang, Lei
    Liao, Shan
    INFORMATION SCIENCES, 2024, 677