Toward parallel intelligence: An interdisciplinary solution for complex systems

Yong Zhao; Zhengqiu Zhu; Bin Chen; Sihang Qiu; Jincai Huang; Xin Lu; Weiyi Yang; Chuan Ai; Kuihua Huang; Cheng He; Yucheng Jin; Zhong Liu; Fei-Yue Wang

The Innovation (Nov 2023)

Toward parallel intelligence: An interdisciplinary solution for complex systems

Yong Zhao,
Zhengqiu Zhu,
Bin Chen,
Sihang Qiu,
Jincai Huang,
Xin Lu,
Weiyi Yang,
Chuan Ai,
Kuihua Huang,
Cheng He,
Yucheng Jin,
Zhong Liu,
Fei-Yue Wang

Affiliations

Yong Zhao: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Zhengqiu Zhu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Bin Chen: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; Hunan Institute of Advanced Technology, Changsha 410073, China
Sihang Qiu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; Corresponding author
Jincai Huang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; Hunan Institute of Advanced Technology, Changsha 410073, China; Corresponding author
Xin Lu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; Corresponding author
Weiyi Yang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Chuan Ai: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Kuihua Huang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; Hunan Institute of Advanced Technology, Changsha 410073, China
Cheng He: Shanghai Institute of Infectious Disease and Biosecurity, Shanghai 200032, China; Institute of Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health (GmbH), Neuherberg, Germany
Yucheng Jin: Department of Computer Science, Hong Kong Baptist University, Hong Kong, China
Zhong Liu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; Hunan Institute of Advanced Technology, Changsha 410073, China
Fei-Yue Wang: State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Journal volume & issue: Vol. 4, no. 6
p. 100521

Abstract

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The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling, analysis, management, and control. To meet these demands, the parallel systems method rooted in the artificial systems, computational experiments, and parallel execution (ACP) approach has been developed. The method cultivates a cycle termed parallel intelligence, which iteratively creates data, acquires knowledge, and refines the actual system. Over the past two decades, the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines, offering versatile interdisciplinary solutions for complex systems across diverse fields. This review explores the origins and fundamental concepts of the parallel systems method, showcasing its accomplishments as a diverse array of parallel technologies and applications while also prognosticating potential challenges. We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.

Published in The Innovation

ISSN: 2666-6758 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Science: Science (General)
Website: https://www.cell.com/the-innovation

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