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International Workshop on Ant Colony Optimization and Swarm Intelligence

ANTS 2006: Ant Colony Optimization and Swarm Intelligence pp 500–501Cite as

A Search Ant and Labor Ant Algorithm for Clustering Data

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4150))

Abstract

In 1990, Deneubourg et al. [1] developed the first ant clustering algorithm based on mimicking corpse piling process of ants. In his algorithm, an ant picks up and drops the data items based on the similarity of ant’s local neighborhoods. Labroche et al. [2] developed a different ant algorithm, AntClust, based on chemical odor and some behavioral rules of ants.

This paper was supported by Faculty Reaserch Fund, Sungkyunkwan University, 2004.

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References

  1. Deneubourg, J.-L., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C., Chrétien, L.: The dynamics of collective sorting: Robot-like ants and ant-like robots. In: Proceedings of the First International Conference on Simulation of Adaptive Behaviour: From Animals to Animats 1, pp. 356–365. MIT Press, Cambridge (1991)

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  2. Labroche, N., Monmarché, N., Venturini, G.: A new clustering algorithm based on the chemical recognition system of ants. In: Proc. ECAI 2002, Lyon, France, pp. 345–349 (2002)

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  3. Lumer, E., Faieta, B.: Diversity and adaptation in populations of clustering ants. In: Proceedings of the Third International Conference on Simulation of Adaptive Behaviour: From Animals to Animats 3, pp. 501–508. MIT Press, Cambridge (1994)

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  4. Handl, J., Knowles, J., Dorigo, M.: Ant-based Clustering and Topographic Mapping. Artificial Life 12(1) (2004)

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Author information

Authors and Affiliations

  1. Sunkyunkwan University, Suwon, Korea

    Heesang Lee, Gyuseok Shim, Yun Bae Kim, Jinsoo Park & Jaebum Kim

Authors
  1. Heesang Lee
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  2. Gyuseok Shim
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  3. Yun Bae Kim
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  4. Jinsoo Park
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  5. Jaebum Kim
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Editor information

Editors and Affiliations

  1. IRIDIA, CoDE, Université Libre de Bruxelles,,, Brussels, Belgium

    Marco Dorigo

  2. Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Lugano, Switzerland

    Luca Maria Gambardella

  3. IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium

    Mauro Birattari

  4. Swarm-Intelligent Systems Group, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland

    Alcherio Martinoli

  5. Department of Computing and Electronic Systems, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Riccardo Poli

  6. IRIDIA, CoDE, Université Libre de Bruxelles, Avenue F. Roosevelt 50, CP 194/6, 1050, Brussels, Belgium

    Thomas Stützle

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Lee, H., Shim, G., Kim, Y.B., Park, J., Kim, J. (2006). A Search Ant and Labor Ant Algorithm for Clustering Data. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_51

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  • DOI: https://doi.org/10.1007/11839088_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38482-3

  • Online ISBN: 978-3-540-38483-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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