Knowledge Commons of Institute of Automation,CAS
Bridging the Micro and Macro: Calibration of Agent-Based Model Using Mean-Field Dynamics | |
Ye, Peijun1; Chen, Yuanyuan1; Zhu, Fenghua1; Lv, Yisheng1; Lu, Wanze2; Wang, Fei-Yue1,3,4 | |
发表期刊 | IEEE TRANSACTIONS ON CYBERNETICS |
ISSN | 2168-2267 |
2021-07-07 | |
卷号 | 99期号:99页码:10 |
摘要 | Calibration of agent-based models (ABM) is an essential stage when they are applied to reproduce the actual behaviors of distributed systems. Unlike traditional methods that suffer from the repeated trial and error and slow convergence of iteration, this article proposes a new ABM calibration approach by establishing a link between agent microbehavioral parameters and systemic macro-observations. With the assumption that the agent behavior can be formulated as a high-order Markovian process, the new approach starts with a search for an optimal transfer probability through a macrostate transfer equation. Then, each agent's microparameter values are computed using mean-field approximation, where his complex dependencies with others are approximated by an expected aggregate state. To compress the agent state space, principal component analysis is also introduced to avoid high dimensions of the macrostate transfer equation. The proposed method is validated in two scenarios: 1) population evolution and 2) urban travel demand analysis. Experimental results demonstrate that compared with the machine-learning surrogate and evolutionary optimization, our method can achieve higher accuracies with much lower computational complexities. |
关键词 | Calibration Computational modeling Mathematical model Machine learning Aggregates Optimization Bayes methods Agent-based model (ABM) calibration Markovian process |
DOI | 10.1109/TCYB.2021.3089712 |
关键词[WOS] | OPTIMIZATION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[62076237] ; National Natural Science Foundation of China[U1811463] ; National Natural Science Foundation of China[61903363] ; Key-Area Research and Development Program of Guangdong Province[2020B0909050001] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2021130] |
项目资助者 | National Natural Science Foundation of China ; Key-Area Research and Development Program of Guangdong Province ; Youth Innovation Promotion Association of Chinese Academy of Sciences |
WOS研究方向 | Automation & Control Systems ; Computer Science |
WOS类目 | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
WOS记录号 | WOS:000732918500001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 人工智能+交通 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/46921 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 中国科学院自动化研究所 |
通讯作者 | Lv, Yisheng |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Beijing Univ Technol, Sch Artificial Intelligence & Automat, Beijing 100124, Peoples R China 3.Qingdao Acad Intelligent Ind, Parallel Intelligence Res Ctr, Qingdao 266109, Peoples R China 4.Macau Univ Sci & Technol, Inst Syst Engn, Macau, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Ye, Peijun,Chen, Yuanyuan,Zhu, Fenghua,et al. Bridging the Micro and Macro: Calibration of Agent-Based Model Using Mean-Field Dynamics[J]. IEEE TRANSACTIONS ON CYBERNETICS,2021,99(99):10. |
APA | Ye, Peijun,Chen, Yuanyuan,Zhu, Fenghua,Lv, Yisheng,Lu, Wanze,&Wang, Fei-Yue.(2021).Bridging the Micro and Macro: Calibration of Agent-Based Model Using Mean-Field Dynamics.IEEE TRANSACTIONS ON CYBERNETICS,99(99),10. |
MLA | Ye, Peijun,et al."Bridging the Micro and Macro: Calibration of Agent-Based Model Using Mean-Field Dynamics".IEEE TRANSACTIONS ON CYBERNETICS 99.99(2021):10. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论