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Volume 11 Issue 5
May  2024

IEEE/CAA Journal of Automatica Sinica

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Article Contents
X. Xue, X. Yu, D. Zhou, X. Wang, C. Bi, S. Wang, and  F.-Y. Wang,  “Computational experiments for complex social systems: Integrated design of experiment system,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1175–1189, May 2024. doi: 10.1109/JAS.2023.123639
Citation: X. Xue, X. Yu, D. Zhou, X. Wang, C. Bi, S. Wang, and  F.-Y. Wang,  “Computational experiments for complex social systems: Integrated design of experiment system,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1175–1189, May 2024. doi: 10.1109/JAS.2023.123639

Computational Experiments for Complex Social Systems: Integrated Design of Experiment System

doi: 10.1109/JAS.2023.123639
Funds:  This work was supported in part by the National Key Research and Development Program of China (2021YFF0900800), the National Natural Science Foundation of China (61972276, 62206116, 62032016), Open Research Fund of The State Key Laboratory for Management and Control of Complex Systems (20210101), New Liberal Arts Reform and Practice Project of National Ministry of Education (2021170002), and Tianjin University Talent Innovation. Reward Program for Literature & Science Graduate Student (C1-2022-010)
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  • Powered by advanced information industry and intelligent technology, more and more complex systems are exhibiting characteristics of the cyber-physical-social systems (CPSS). And human factors have become crucial in the operations of complex social systems. Traditional mechanical analysis and social simulations alone are powerless for analyzing complex social systems. Against this backdrop, computational experiments have emerged as a new method for quantitative analysis of complex social systems by combining social simulation (e.g., ABM), complexity science, and domain knowledge. However, in the process of applying computational experiments, the construction of experiment system not only considers a large number of artificial society models, but also involves a large amount of data and knowledge. As a result, how to integrate various data, model and knowledge to achieve a running experiment system has become a key challenge. This paper proposes an integrated design framework of computational experiment system, which is composed of four parts: generation of digital subject, generation of digital object, design of operation engine, and construction of experiment system. Finally, this paper outlines a typical case study of coal mine emergency management to verify the validity of the proposed framework.

     

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    Highlights

    • This article presents solutions to two main questions: 1) how to convert descriptive artificial society models into functional computational experiments, and 2) how to incorporate new technologies into these artificial society models. The article also proposes an integrated design framework for computational experiment systems that involves four key steps: generating digital subjects (such as agents or digital humans), generating digital objects (such as social or physical environments), designing the operation engine, and constructing the experiment system.

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