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Cognitive Intelligence: Deep Learning, Thinking, and Reasoning by Brain-Inspired Systems

Author

Listed:
  • Yingxu Wang

    (International Institute of Cognitive Informatics and Cognitive Computing (ICIC),Laboratory for Computational Intelligence, Denotational Mathematics, and Software Science, Department of Electrical and Computer Engineering, Schulich School of Engineering and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada & Information Systems Lab, Stanford University, Stanford, CA, USA)

  • Bernard Widrow

    (Stanford University, Stanford, CA, USA)

  • Lotfi A. Zadeh

    (UC Berkeley, Berkeley, CA, USA)

  • Newton Howard

    (University of Oxford, Oxford, UK)

  • Sally Wood

    (Santa Clara University, Santa Carla, CA, USA)

  • Virendrakumar C. Bhavsar

    (University of New Brunswick, Fredericton, Canada)

  • Gerhard Budin

    (Center for Translation Studies, Vienna University, Vienna, Austria)

  • Christine Chan

    (University of Regina, Regina, Canada)

  • Rodolfo A. Fiorini

    (Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano University, Milano, Italy)

  • Marina L. Gavrilova

    (Department of Computer Science, University of Calgary, Calgary, Canada)

  • Duane F. Shell

    (Department of Educational Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA)

Abstract

The theme of IEEE ICCI*CC'16 on Cognitive Informatics (CI) and Cognitive Computing (CC) was on cognitive computers, big data cognition, and machine learning. CI and CC are a contemporary field not only for basic studies on the brain, computational intelligence theories, and denotational mathematics, but also for engineering applications in cognitive systems towards deep learning, deep thinking, and deep reasoning. This paper reports a set of position statements presented in the plenary panel (Part I) in IEEE ICCI*CC'16 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.

Suggested Citation

  • Yingxu Wang & Bernard Widrow & Lotfi A. Zadeh & Newton Howard & Sally Wood & Virendrakumar C. Bhavsar & Gerhard Budin & Christine Chan & Rodolfo A. Fiorini & Marina L. Gavrilova & Duane F. Shell, 2016. "Cognitive Intelligence: Deep Learning, Thinking, and Reasoning by Brain-Inspired Systems," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 10(4), pages 1-20, October.
    • Handle: RePEc:igg:jcini0:v:10:y:2016:i:4:p:1-20
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    Cited by:

    1. Aswani Kumar Cherukuri & Radhika Shivhare & Ajith Abraham & Jinhai Li & Annapurna Jonnalagadda, 2021. "A Pragmatic Approach to Understand Hebbian Cell Assembly," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 15(2), pages 60-82, April.
    2. Aswani Kumar Cherukuri & Radhika Shivhare & Ajith Abraham & Jinhai Li & Annapurna Jonnalagadda, 2021. "A Pragmatic Approach to Understand Hebbian Cell Assembly," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 15(2), pages 73-95, April.
    3. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.

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