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Toward parallel intelligence: An interdisciplinary solution for complex systems
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DOI：10.1016/j.xinn.2023.100521.png)
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Abstract
En 中文
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 applica-tions while also prognosticating potential challenges. We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.
Keywords:
COMPUTATIONAL SOCIAL-SCIENCE
OF-THE-ART
TRANSPORTATION SYSTEMS
KNOWLEDGE AUTOMATION
AUTONOMOUS VEHICLES
EVACUATION
FRAMEWORK
ORGANIZATIONS
METAVERSES
SCENARIOS
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