Abstract Intelligence

Author:

Wang Yingxu1,Zadeh Lotfi A.2,Widrow Bernard3,Howard Newton4,Beaufays Françoise5,Baciu George6,Hsu D. Frank7,Luo Guiming8,Mizoguchi Fumio9,Patel Shushma10,Raskin Victor11,Tsumoto Shusaku12,Wei Wei3,Zhang Du13

Affiliation:

1. International Institute of Cognitive Informatics and Cognitive Computing (ICIC), University of Calgary, Calgary, Canada

2. UC Berkeley, Berkeley, USA

3. Stanford University, Stanford, USA

4. University of Oxford, Oxford, UK

5. Google, Mountain View, USA

6. GAMA Lab, Department of Computing, Hong Kong Polytechnic University, Hung Hom, Hong Kong

7. Fordham University, New York City, USA

8. School of Software, Tsinghua University, Beijing, China

9. Tokyo University of Science, Tokyo, Japan

10. Faculty of Business, London South Bank University, London, UK

11. LING/CERIAS/CS/CIT, Purdue University, West Lafayette, USA

12. Department of Medical Informatics, Faculty of Medicine, Shimane University, Matsue, Japan

13. Macau University of Science and Technology, Taipa, Macau

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.

Publisher

IGI Global

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