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Cognition-Inspired Fuzzy Modelling

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Advances in Computational Intelligence (WCCI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7311))

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Abstract

This chapter presents different notions used for fuzzy modelling that formalize fundamental concepts used in cognitive psychology. From a cognitive point of view, the tasks of categorization, pattern recognition or generalization lie in the notions of similarity, resemblance or prototypes. The same tasks are crucial in Artificial Intelligence to reproduce human behaviors. As most real world concepts are messy and open-textured, fuzzy logic and fuzzy set theory can be the relevant framework to model all these key notions.

On the basis of the essential works of Rosch and Tversky, and on the critics formulated on the inadequacy of fuzzy logic to model cognitive concepts, we study a formal and computational approach of the notions of similarity, typicality and prototype, using fuzzy set theory. We propose a framework to understand the different properties and possible behaviors of various families of similarities. We highlight their semantic specifics and we propose numerical tools to quantify these differences, considering different views. We propose also an algorithm for the construction of fuzzy prototypes that can be extended to a classification method.

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Author information

Authors and Affiliations

  1. UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France

    Maria Rifqi

  2. CNRS, UMR 7606, LIP6, F-75005, Paris, France

    Maria Rifqi

  3. Université Panthéon-Assas - Paris 2, F-75005, Paris, France

    Maria Rifqi

Authors
  1. Maria Rifqi
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Editor information

Editors and Affiliations

  1. Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, 710071, Xi’an, Shaanxi, China

    Jing Liu

  2. Dipartimento di Elettronica e Informazione, Politecnico di Milano, 20133, Milano, Italy

    Cesare Alippi

  3. Université Pierre et Marie Curie - Paris 6, LIP6, 4 place Jussieu, 75005, Paris, France

    Bernadette Bouchon-Meunier

  4. Department of Electrical & Computer Engineering, Portland State University, 97207, Portland, OR, USA

    Garrison W. Greenwood

  5. School of Engineering and Information Technology, University of New South Wales, 2600, Canberra, ACT, Australia

    Hussein A. Abbass

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Rifqi, M. (2012). Cognition-Inspired Fuzzy Modelling. In: Liu, J., Alippi, C., Bouchon-Meunier, B., Greenwood, G.W., Abbass, H.A. (eds) Advances in Computational Intelligence. WCCI 2012. Lecture Notes in Computer Science, vol 7311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30687-7_9

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  • DOI: https://doi.org/10.1007/978-3-642-30687-7_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30686-0

  • Online ISBN: 978-3-642-30687-7

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