Hybrid-augmented intelligence: collaboration and cognition
Zheng, Nan-ning1,2; Liu, Zi-yi1,2; Ren, Peng-ju1,2; Ma, Yong-qiang1,2; Chen, Shi-tao1,2; Yu, Si-yu1,2; Xue, Jian-ru1,2; Chen, Ba-dong1,2; Wang, Fei-yue3
Source PublicationFRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
2017-02-01
Volume18Issue:2Pages:153-179
SubtypeReview
AbstractThe 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.
KeywordHuman-machine Collaboration Hybrid-augmented Intelligence Cognitive Computing Intuitive Reasoning Causal Model Cognitive Mapping Visual Scene Understanding Self-driving Cars
WOS HeadingsScience & Technology ; Technology
DOI10.1631/FITEE.1700053
WOS KeywordUNMANNED AERIAL VEHICLE ; ARTIFICIAL-INTELLIGENCE ; NEURAL-NETWORKS ; IBM WATSON ; BIG DATA ; SYSTEMS ; CAUSALITY ; MEMORY ; RECOGNITION ; PERCEPTION
Indexed BySCI ; SSCI
Language英语
Funding OrganizationChinese Academy of Engineering ; National Natural Science Foundation of China(L1522023) ; National Basic Research Program (973) of China(2015CB351703) ; National Key Research and Development Plan(2016YFB1001004 ; 2016YFB1000903)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Engineering, Electrical & Electronic
WOS IDWOS:000394541400001
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14422
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Affiliation1.Xi An Jiao Tong Univ, Inst Artificial Intelligence & Robot, Xian 710049, Peoples R China
2.Xi An Jiao Tong Univ, Natl Engn Lab Visual Informat Proc Applicat, Xian 710049, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zheng, Nan-ning,Liu, Zi-yi,Ren, Peng-ju,et al. Hybrid-augmented intelligence: collaboration and cognition[J]. FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING,2017,18(2):153-179.
APA Zheng, Nan-ning.,Liu, Zi-yi.,Ren, Peng-ju.,Ma, Yong-qiang.,Chen, Shi-tao.,...&Wang, Fei-yue.(2017).Hybrid-augmented intelligence: collaboration and cognition.FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING,18(2),153-179.
MLA Zheng, Nan-ning,et al."Hybrid-augmented intelligence: collaboration and cognition".FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING 18.2(2017):153-179.
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