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Inspiration for optimization from social insect behaviour

Nature volume 406, pages 39–42 (2000)Cite this article

Abstract

Research in social insect behaviour has provided computer scientists with powerful methods for designing distributed control and optimization algorithms. These techniques are being applied successfully to a variety of scientific and engineering problems. In addition to achieving good performance on a wide spectrum of ‘static’ problems, such techniques tend to exhibit a high degree of flexibility and robustness in a dynamic environment.

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Figure 1: Typical result of a comparison of AntNet, an Ant Colony Routing algorithm, with other widespread routing algorithms for packet-switched networks (see ref.41 for an overview of communications networks).

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Acknowledgements

E. B. is supported by the Interval Research Fellowship at the Santa Fe Institute. E. B. and G.T. are supported in part by a grant from the GIS (Groupement d'Intérêt Scientifique) Sciences de la Cognition. G. T. is supported by a grant from the Conseil Régional Midi-Pyrénées. M. D. acknowledges support from the Belgian FNRS, of which he is a Research Associate.

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Authors and Affiliations

  1. Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, 87501, New Mexico, USA

    E. Bonabeau

  2. Eurobios, Tour Ernst & Young, La Défense Cédex, 92037, France

    E. Bonabeau

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

    M. Dorigo

  4. Laboratoire d’Ethologie et Cognition Animale, CNRS-FRE 2041, Université Paul Sabatier, 118 Route de Narbonne, Toulouse Cédex, 31062, France

    G. Theraulaz

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  1. E. Bonabeau
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  3. G. Theraulaz
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Correspondence to E. Bonabeau.

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Bonabeau, E., Dorigo, M. & Theraulaz, G. Inspiration for optimization from social insect behaviour. Nature 406, 39–42 (2000). https://doi.org/10.1038/35017500

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