Toward parallel intelligence: an interdisciplinary solution for complex systems
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 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.
Cite
@article{arxiv.2311.12838,
title = {Toward parallel intelligence: an interdisciplinary solution for complex systems},
author = {Yong Zhao and Zhengqiu Zhu and Bin Chen and Sihang Qiu and Jincai Huang and Xin Lu and Weiyi Yang and Chuan Ai and Kuihua Huang and Cheng He and Yucheng Jin and Zhong Liu and Fei-Yue Wang},
journal= {arXiv preprint arXiv:2311.12838},
year = {2024}
}
Comments
41 pages, 6 figures. The Innovation (2023)