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Learning Systems with FUZZY

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Fifty Years of Fuzzy Logic and its Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 326))

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Abstract

Fuzzy techniques have been proven to effectively tackle the problems of uncertainty in relationships among variables in systems that learn to adapt to a changing environment. This paper outlines our challenges for the last 25 years to design learning systems with fuzzy techniques and their applications to many real world problems. We then focus on the development of human-in-the-loop systems, such as a smart home or an assistive robotic environment, that involve different types of learning strategies. This warrants a full consideration of learning mechanisms in humans that mediate action-selection. We envisage that the principles of fuzzy theory, when combined with what we know about computational learning mechanisms in the human brain, will offer a practical guidance on how we design learning systems to advance user’s experience in real-world scenarios.

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Author information

Authors and Affiliations

  1. Computation & Neural Systems, California Institute of Technology, Pasadena, USA

    Sang Wan Lee

  2. Department of Electrical Engineering, KAIST, Daejeon, Republic of Korea

    Z. Zenn Bien

Authors
  1. Sang Wan Lee
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  2. Z. Zenn Bien
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Correspondence to Sang Wan Lee .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas State University, San Marcos, Texas, USA

    Dan E. Tamir

  2. School of Computing and Information Sciences, Florida International University, Miami, Florida, USA

    Naphtali D. Rishe

  3. School of Computing and Information Sciences, The University of South Florida, Tampa, Florida, USA, and Florida International University, Miami, Florida, USA

    Abraham Kandel

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© 2015 Springer International Publishing Switzerland

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Lee, S.W., Zenn Bien, Z. (2015). Learning Systems with FUZZY. In: Tamir, D., Rishe, N., Kandel, A. (eds) Fifty Years of Fuzzy Logic and its Applications. Studies in Fuzziness and Soft Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-19683-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-19683-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19682-4

  • Online ISBN: 978-3-319-19683-1

  • eBook Packages: EngineeringEngineering (R0)

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