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A Parallel Cellular Ant Colony Algorithm for Clustering and Sorting

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2493))

Abstract

Some ant species are known to gather and sort corpses in an auto-organized way. In this contribution, we propose a new cellular ant colony algorithm for sorting and clustering. This algorithm mimics the behavior of real ants. The cellular automata nature of our algorithm implies a straightforward parallelization. The rule consists of a pick-up, a deposition and a diffusion. Our probabilistic pick-up rule is based on some spatial neighborhood information. We observe that probabilistic pick-up yields compact clusters and also speeds up the clustering process. In the long run, a single cluster emerges. Moreover, in the presence of several corpse species, our algorithm sorts the corpses into distinct clusters. Thus our model reproduces realistic results, but however we do not observe any collective effect.

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References

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© 2002 Springer-Verlag Berlin Heidelberg

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Albuquerque, P., Dupuis, A. (2002). A Parallel Cellular Ant Colony Algorithm for Clustering and Sorting. In: Bandini, S., Chopard, B., Tomassini, M. (eds) Cellular Automata. ACRI 2002. Lecture Notes in Computer Science, vol 2493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45830-1_21

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  • DOI: https://doi.org/10.1007/3-540-45830-1_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44304-9

  • Online ISBN: 978-3-540-45830-2

  • eBook Packages: Springer Book Archive

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