Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65975
Title: Abstract intelligence : embodying and enabling cognitive systems by mathematical engineering
Authors: Wang, Y
Zadeh, LA
Widrow, B
Howard, N
Beaufays, F
Baciu, G
Hsu, DF
Luo, G
Mizoguchi, F
Patel, S
Raskin, V
Tsumoto, S
Wei, W
Zhang, D
Keywords: Abstract intelligence
Applications
Artificial intelligence
Brain-inspired systems
Cognitive computers
Cognitive engineering
Cognitive informatics
Cognitive robotics
Cognitive systems
Computational intelligence
Denotational mathematics
Mathematical engineering
Issue Date: 2017
Publisher: IGI Global
Source: International journal of cognitive informatics and natural intelligence, 2017, v. 11, no. 1, p. 1-15 How to cite?
Journal: International journal of cognitive informatics and natural intelligence 
Abstract: Basic studies in denotational mathematics and mathematical engineering have led to the theory of abstract intelligence (aI), which is a set of mathematical models of natural and computational intelligence in cognitive informatics (CI) and cognitive computing (CC). Abstract intelligence triggers the recent breakthroughs in cognitive systems such as cognitive computers, cognitive robots, cognitive neural networks, and cognitive learning. This paper reports a set of position statements presented in the plenary panel (Part II) of IEEE ICCI∗CC'16 on Cognitive Informatics and Cognitive Computing at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.
URI: http://hdl.handle.net/10397/65975
ISSN: 1557-3958
EISSN: 1557-3966
DOI: 10.4018/IJCINI.2017010101
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