Abstract intelligence: Embodying and enabling cognitive systems by mathematical engineering

Yingxu Wang, Lotfi A. Zadeh, Bernard Widrow, Newton Howard, Françoise Beaufays, George Baciu, D. Frank Hsu, Guiming Luo, Fumio Mizoguchi, Shushma Patel, Victor Raskin, Shusaku Tsumoto, Wei Wei, Du Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

12 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalInternational Journal of Cognitive Informatics and Natural Intelligence
Volume11
Issue number1
DOIs
Publication statusPublished - 1 Jan 2017

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

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Artificial Intelligence

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