Computational Experiments for Complex Social Systems—Part III

The Docking of Domain Models

Dados Bibliográficos

ID22108251
AutoresXiao Xue (0000-0003-1204-9883, Tianjin University), Xiangning Yu (Tianjin University), Deyu Zhou (0000-0002-1150-7662, Shandong University), Chao Peng (0009-0009-9669-8928, Tianjin University), Xiao Wang (0000-0001-8231-6778, Chinese Academy of Sciences), Donghua Liu (0000-0002-1108-257X, China Waterborne Transport Research Institute), Fei‐yue Wang (0000-0001-9185-3989, Chinese Academy of Sciences)
Ano2024
Volume11
Fascículo2
Páginas1766-1780
Data de publicação2024-04-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoIEEE Transactions on Computational Social Systems (JOURNAL)
Identificadores do periódicoISSN: 2329-924X • E-ISSN: 2373-7476
EditoraInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2023.3243894
OpenAlexW4321608016
IdiomaEN
Citações recebidas1
Referências citadas31

Powered by advanced information technology, more and more complex systems are exhibiting characteristics of the cyber–physical–social systems (CPSS). In consideration of the cost, legal, and institutional constraints on the study of CPSS in real world, computational experiments have emerged as a new method for quantitative analysis of CPSS. However, with the increase of application scenarios, how to map complex and diverse domain models to artificial society models has become a key challenge to hinder the wide use of computational experiments. In this article, the docking framework between the domain model and the artificial society model was proposed in this article, and the model docking specification is given from three aspects: the agent model, the environmental model, and the rules model. In addition, the effectiveness of the framework was verified by two classic cases: artificial stock market and epidemic prevention and control. The result showed that the proposed model docking framework can provide technical support for the multidisciplinary applications of computational experiments and significantly reduce the difficulty of using the method

Complex system · Computational model · Management science · Multidisciplinary approach · Social system · Complex Systems and Time Series Analysis · Computer Science · Data Visualization and Analytics · Engineering · Time Series Analysis and Forecasting · Artificial Intelligence