LAPSE:2023.5803
Published Article
LAPSE:2023.5803
Understanding the Evolution and Applications of Intelligent Systems via a Tri-X Intelligence (TI) Model
Min Zhao, Zhenbo Ning, Baicun Wang, Chen Peng, Xingyu Li, Sihan Huang
February 23, 2023
The evolution and application of intelligence have been discussed from perspectives of life, control theory and artificial intelligence. However, there has been no consensus on understanding the evolution of intelligence. In this study, we propose a Tri-X Intelligence (TI) model, aimed at providing a comprehensive perspective to understand complex intelligence and the implementation of intelligent systems. In this work, the essence and evolution of intelligent systems (or system intelligentization) are analyzed and discussed from multiple perspectives and at different stages (Type I, Type II and Type III), based on a Tri-X Intelligence model. Elemental intelligence based on scientific effects (e.g., conscious humans, cyber entities and physical objects) is at the primitive level of intelligence (Type I). Integrated intelligence formed by two-element integration (e.g., human-cyber systems and cyber-physical systems) is at the normal level of intelligence (Type II). Complex intelligence formed by ternary-interaction (e.g., a human-cyber-physical system) is at the dynamic level of intelligence (Type III). Representative cases are analyzed to deepen the understanding of intelligent systems and their future implementation, such as in intelligent manufacturing. This work provides a systematic scheme, and technical supports, to understand and develop intelligent systems.
Keywords
cyber-physical systems, human-cyber systems, intelligent manufacturing, intelligent systems, Tri-X Intelligence
Suggested Citation
Zhao M, Ning Z, Wang B, Peng C, Li X, Huang S. Understanding the Evolution and Applications of Intelligent Systems via a Tri-X Intelligence (TI) Model. (2023). LAPSE:2023.5803
Author Affiliations
Zhao M: Towards-Intelligence Research Institute, Beijing 100085, China
Ning Z: Towards-Intelligence Research Institute, Beijing 100085, China
Wang B: State Key Lab of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China [ORCID]
Peng C: State Key Lab of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
Li X: Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48105, USA
Huang S: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Journal Name
Processes
Volume
9
Issue
6
First Page
1080
Year
2021
Publication Date
2021-06-21
Published Version
ISSN
2227-9717
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PII: pr9061080, Publication Type: Journal Article
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doi:10.3390/pr9061080
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Feb 23, 2023
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