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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2100418


Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management and control for complex systems


Author(s):  Feiyue WANG, Jianbo GUO, Guangquan BU, Jun ZHANG

Affiliation(s):  The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; more

Corresponding email(s):   jun.zhang.ee@whu.edu.cn

Key Words:  Complex systems, Human-machine knowledge automation, Parallel systems, Bulk power grid dispatch, Artificial intelligence, Internet of minds


Feiyue WANG, Jianbo GUO, Guangquan BU, Jun 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, 1998, -1(-1): .

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%T Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management and control for complex systems
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Abstract: 
This article aims 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 begin with a description of the historical development of complex system science and analyze the limitations of human 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 trust-worthy HM-KA" concept can provide a novel and canonical mechanism, and benefit real-world practices of complex system cogni-tion, management, and control.

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