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Mapping Artificial Immune Systems into Learning Classifier Systems

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Learning Classifier Systems (IWLCS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2661))

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Abstract

This paper presents one form of mapping Artificial Immune Systems (AIS) into Learning Classifier Systems (LCS). Artificial Immune Systems can be defined as adaptive systems inspired by theoretical models and principles of the biological immune system and applied to solve problems in the most diverse domains, from biology to computing. Similar to Learning Classifier Systems, already used to model complex adaptive systems, a better understanding of Artificial Immune Systems can be obtained when they are analysed under the perspective of complex adaptive systems. One of the goals here is to determine complementary features of both systems (LCS and AIS), aiming at providing a novel mapping conception. The formal treatment proposed along the paper may then be used to integrate models for complex adaptive systems.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering, State University of Campinas (Unicamp), Campinas-SP, Brazil

    Patrícia A. Vargas, Leandro N. de Castro & Fernando J. Von Zuben

Authors
  1. Patrícia A. Vargas
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  2. Leandro N. de Castro
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  3. Fernando J. Von Zuben
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Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano, Italy

    Pier Luca Lanzi

  2. Daimler Chrysler AG, 71059, Sindelfingen, Germany

    Wolfgang Stolzmann

  3. Prediction Dynamics, Concord MA 01742 USA, Department of General Engineering, The University of Illinois at Urbana-Champaign, IL 61801, USA

    Stewart W. Wilson

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Vargas, P.A., de Castro, L.N., Von Zuben, F.J. (2003). Mapping Artificial Immune Systems into Learning Classifier Systems. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Learning Classifier Systems. IWLCS 2002. Lecture Notes in Computer Science(), vol 2661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-40029-5_10

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  • DOI: https://doi.org/10.1007/978-3-540-40029-5_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20544-9

  • Online ISBN: 978-3-540-40029-5

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