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Fuzzy and Crisp Representations of Real-Valued Input for Learning Classifier Systems

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Learning Classifier Systems (IWLCS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1813))

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Abstract

We discuss some issues concerning the application of learning classifier systems to real-valued applications. In particular, we focus on the possibility of classifying data by crisp and fuzzy intervals, showing the effect of their granularity on the learning performance. We introduce the concept of sensorial cluster and we discuss the difference between cluster aliasing and perceptual aliasing. We show the impact of different choices on the performance of both crisp and fuzzy learning classifier systems applied to a mobile, autonomous, robotic agent.

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Author information

Authors and Affiliations

  1. Politecnico di Milano AI and Robotics Project, Dipartimento di Elettronica e Informazione, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milano, Italy

    Andrea Bonarini, Claudio Bonacina & Matteo Matteucci

Authors
  1. Andrea Bonarini
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  2. Claudio Bonacina
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  3. Matteo Matteucci
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Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica ed Informatzione, Politecnico di Milano, Piazza Leonardo da Vinci n. 32, 20133, Milano, Italy

    Pier Luca Lanzi

  2. Institut für Psychologie III, Universität Würzburg, Röntgenring 11, 97070, Würzburg, Germany

    Wolfgang Stolzmann

  3. Prediction Dynamics, Concord, MA, 01742, USA

    Stewart W. Wilson

  4. Department of General Engineering, University of Illinois at Urbana-Champaign, USA

    Stewart W. Wilson

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© 2000 Springer-Verlag Berlin Heidelberg

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Bonarini, A., Bonacina, C., Matteucci, M. (2000). Fuzzy and Crisp Representations of Real-Valued Input for Learning Classifier Systems. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Learning Classifier Systems. IWLCS 1999. Lecture Notes in Computer Science(), vol 1813. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45027-0_5

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  • DOI: https://doi.org/10.1007/3-540-45027-0_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67729-1

  • Online ISBN: 978-3-540-45027-6

  • eBook Packages: Springer Book Archive

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