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

Xiao Xue; Xiangning Yu; Deyu Zhou; Xiao Wang; Chongke Bi; Shufang Wang; Fei-Yue Wang

doi:10.1109/JAS.2023.123639

Volume 11 Issue 5

May 2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2024 > 11(5): 1175-1189

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

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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

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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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Author Bio:
Xiao Xue is a Professor at the School of Computer Software, College of Intelligence and Computing, Tianjin University, also an Adjunct Professor with the Information School, Xi’an University of Financial and Economics. His main research interests include service computing, computational experiment, crowd intelligence and social computing, etc

Xiangning Yu is a Ph.D. candidate at the College of Intelligence and Computing, Tianjin University. Her current research interests include service computing and computational experiments

Deyu Zhou is a Ph.D. candidate at the School of Software, Shandong University. Her research interests cover service computing and computational experiments

Xiao Wang received the B.E degree in network engineering from the Dalian University of Technology in 2011, the M.E. and Ph.D. degrees in social computing from the University of Chinese Academy of Sciences in 2016. She is a Professor at Anhui University. She is also at the Qingdao Academy of Intelligent Industries. Her research interests include social computing, knowledge automation, parallel intelligence, autonomous driving and ITS, SciTS, and DAO-based computational social systems

Chongke Bi is a Professor in the College of Intelligence and Computing, Tianjin University. His current research interests include scientific visualization and high performance computing

Shufang Wang is a Professor and master Supervisor in the School of Geographic and Environmental Sciences, Tianjin Normal University. Her main research interests include human geography and computational experiment, etc

Fei-Yue Wang (Fellow, IEEE) received the Ph.D. degree in computer and systems engineering from the Rensselaer Polytechnic Institute, USA, in 1990. He joined the University of Arizona, USA, in 1990 and became a Professor and the Director of the Robotics and Automation Laboratory and the Program in Advanced Research for Complex Systems. In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), under the support of the Outstanding Chinese Talents Program from the State Planning Council, and in 2002, was appointed as the Director of the Key Laboratory of Complex Systems and Intelligence Science, CAS, and Vice President of Institute of Automation, CAS in 2006. He found CAS Center for Social Computing and Parallel Management in 2008, and became the State Specially Appointed Expert and the Founding Director of the State Key Laboratory for Management and Control of Complex Systems in 2011. His current research focuses on methods and applications for parallel intelligence, social computing, and knowledge automation. He is a Fellow of INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China, numerous best papers awards from IEEE Transactions, and became an Outstanding Scientist of ACM for his work in intelligent control and social computing. He received the IEEE ITS Outstanding Application and Research Awards in 2009, 2011, and 2015, respectively, the IEEE SMC Norbert Wiener Award in 2014, and became the IFAC Pavel J. Nowacki Distinguished Lecturer in 2021. Since 1997, he has been serving as the General or Program Chair of over 30 IEEE, INFORMS, IFAC, ACM, and ASME conferences. He was the President of the IEEE ITS Society from 2005 to 2007, the IEEE Council of RFID from 2019 to 2021, the Chinese Association for Science and Technology, USA, in 2005, the American Zhu Kezhen Education Foundation from 2007 to 2008, the Vice President of the ACM China Council from 2010 to 2011, the Vice President and the Secretary General of the Chinese Association of Automation from 2008 to 2018, the Vice President of IEEE Systems, Man, and Cybernetics Society from 2019 to 2021. He was the Founding Editor-in-Chief (EiC) of the International Journal of Intelligent Control and Systems from 1995 to 2000, IEEE ITS Magazine from 2006 to 2007, IEEE/CAA Journal of Automatica Sinica from 2014–2017, China’s Journal of Command and Control from 2015–2021, and China’s Journal of Intelligent Science and Technology from 2019 to 2021. He was the EiC of the IEEE Intelligent Systems from 2009 to 2012, IEEE Transactions on Intelligent Transportation Systems from 2009 to 2016, IEEE Transactions on Computational Social Systems from 2017 to 2020. Currently, he is the President of CAA’s Supervision Council, and the EiC of IEEE Transaction on Intelligent Vehicles
Corresponding author: Xiao Xue, e-mail: jzxuexiao@tju.edu.cn
Received Date: 2023-03-28
Revised Date: 2023-04-17
Accepted Date: 2023-04-19

Available Online: 2024-02-23

Abstract

Abstract

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.
- Artificial society,
- computational experiments,
- model integration,
- operation engine,
- technology integration

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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.

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

doi: 10.1109/JAS.2023.123639

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