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

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number100521
JournalInnovation
Volume4
Issue number6
Early online date5 Oct 2023
DOIs
Publication statusPublished - 13 Nov 2023

Scopus Subject Areas

  • General

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