CLC number: TP11
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2022-08-29
Cited: 0
Clicked: 4414
Citations: Bibtex RefMan EndNote GB/T7714
Fei-Yue WANG, Jianbo GUO, Guangquan BU, Jun Jason ZHANG. Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(8): 1142-1157.
@article{title="Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems",
author="Fei-Yue WANG, Jianbo GUO, Guangquan BU, Jun Jason ZHANG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="23",
number="8",
pages="1142-1157",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2100418"
}
%0 Journal Article
%T Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems
%A Fei-Yue WANG
%A Jianbo GUO
%A Guangquan BU
%A Jun Jason ZHANG
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 8
%P 1142-1157
%@ 2095-9184
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2100418
TY - JOUR
T1 - Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems
A1 - Fei-Yue WANG
A1 - Jianbo GUO
A1 - Guangquan BU
A1 - Jun Jason ZHANG
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 8
SP - 1142
EP - 1157
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2100418
Abstract: In this paper, we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation (HM-KA) as the technical mechanism of hybrid augmented intelligence (HAI) based complex system cognition, management, and control (CMC). We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence. The need for using human-machine HAI in complex systems is then explained in detail. The concept of “mutually trustworthy HM-KA” mechanism is proposed to tackle the CMC challenge, and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch. It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.
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