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Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

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Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computa-tional experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of"algorithmization"of"counterfactuals".However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper pro-poses an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response vari-ables of the system by means of the modeling of an artificial soci-ety;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on"rider race".

Agent-based modelingcomputational experimentscyber-physical-social systems(CPSS)generative deductiongenera-tive experimentsmeta model

Xiao Xue、Deyu Zhou、Xiangning Yu、Gang Wang、Juanjuan Li、Xia Xie、Lizhen Cui、Fei-Yue Wang

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School of Computer Software, College of Intelligence and Computing, Tianjin University, Tianjin 300350, China

School of Software and the Joint SDUNTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan 250101, China

Information School, Xi'an University of Financial and Economics, Xi'an 710100, China

State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing100190, China

Hainan University, Haikou 570228, China

State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 1001901, China

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国家重点研发计划国家自然科学基金国家自然科学基金国家自然科学基金New Liberal Arts Reform and Practice Project of National Ministry of EducationOpen Research Fund of the State Key Laboratory for Management and Control of Complex SystemsTianjin University Talent Innovation Reward Program for Literature and Science Graduate Student

2021YFF0900800619722766220611662032016202117000220210 101C1-2022-010

2024

10.1109/JAS.2024.124221

自动化学报(英文版)
中国自动化学会,中国科学院自动化研究所,中国科技出版传媒股份有限公司

自动化学报(英文版)

CSTPCDEI
ISSN：2329-9266
年,卷(期)：2024.11(4)
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