CLC number: TP18
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2017-01-22
Cited: 0
Clicked: 8255
Nan-ning Zheng, Zi-yi Liu, Peng-ju Ren, Yong-qiang Ma, Shi-tao Chen, Si-yu Yu, Jian-ru Xue, Ba-dong Chen, Fei-yue Wang. Hybrid-augmented intelligence: collaboration and cognition[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(2): 153-179.
@article{title="Hybrid-augmented intelligence: collaboration and cognition",
author="Nan-ning Zheng, Zi-yi Liu, Peng-ju Ren, Yong-qiang Ma, Shi-tao Chen, Si-yu Yu, Jian-ru Xue, Ba-dong Chen, Fei-yue Wang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="2",
pages="153-179",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700053"
}
%0 Journal Article
%T Hybrid-augmented intelligence: collaboration and cognition
%A Nan-ning Zheng
%A Zi-yi Liu
%A Peng-ju Ren
%A Yong-qiang Ma
%A Shi-tao Chen
%A Si-yu Yu
%A Jian-ru Xue
%A Ba-dong Chen
%A Fei-yue Wang
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 2
%P 153-179
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700053
TY - JOUR
T1 - Hybrid-augmented intelligence: collaboration and cognition
A1 - Nan-ning Zheng
A1 - Zi-yi Liu
A1 - Peng-ju Ren
A1 - Yong-qiang Ma
A1 - Shi-tao Chen
A1 - Si-yu Yu
A1 - Jian-ru Xue
A1 - Ba-dong Chen
A1 - Fei-yue Wang
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 2
SP - 153
EP - 179
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1700053
Abstract: The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. hybrid-augmented intelligence can be divided into two basic models: one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.
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