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Swarm Intelligence

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Handbook of Natural Computing

Abstract

Increasing numbers of books, websites, and articles are devoted to the concept of “swarm intelligence.” Meanwhile, a perhaps confusing variety of computational techniques are seen to be associated with this term, such as “agents,” “emergence,” “boids,” “ant colony optimization,” and so forth. In this chapter, we attempt to clarify the concept of swarm intelligence and its associations, and to provide a perspective on its inspirations, history, and current state. We focus on the most popular and successful algorithms that are associated with swarm intelligence, namely, ant colony optimization, particle swarm optimization, and (more recently) foraging algorithms, and we cover the sources of natural inspiration with these foci in mind. We then round off the chapter with a brief review of current trends.

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Author information

Authors and Affiliations

  1. School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK

    David W. Corne

  2. School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK

    Alan Reynolds

  3. Icosystem Corporation, Cambridge, MA, USA

    Eric Bonabeau

Authors
  1. David W. Corne
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  2. Alan Reynolds
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  3. Eric Bonabeau
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Editor information

Editors and Affiliations

  1. LIACS, Leiden University, Leiden, The Netherlands

    Grzegorz Rozenberg

  2. Computer Science Department, University of Colorado, Boulder, USA

    Grzegorz Rozenberg

  3. LIACS, Leiden University, Leiden, The Netherlands

    Thomas Bäck

  4. LIACS, Leiden University, Leiden, The Netherlands

    Joost N. Kok

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Corne, D.W., Reynolds, A., Bonabeau, E. (2012). Swarm Intelligence. In: Rozenberg, G., Bäck, T., Kok, J.N. (eds) Handbook of Natural Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92910-9_48

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