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.
['Yingxu Wang', 'Lotfi A. Zadeh', 'Bernard Widrow', 'Newton Howard', 'FranÃ§oise Beaufays', 'George Baciu', 'D. Frank Hsu', 'Guiming Luo', 'Fumio Mizoguchi', 'Shushma Patel', 'Victor Raskin', 'Shusaku Tsumoto', 'Wei Wei', 'Du Zhang']
Abstract Intelligence: Embodying and Enabling Cognitive Systems by Mathematical Engineering