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Coevolutionary Principles

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Handbook of Natural Computing

Abstract

Coevolutionary algorithms approach problems for which no function for evaluating potential solutions is present or known. Instead, algorithms rely on the aggregation of outcomes from interactions among evolving entities in order to make selection decisions. Given the lack of an explicit yardstick, understanding the dynamics of coevolutionary algorithms, judging whether a given algorithm is progressing, and designing effective new algorithms present unique challenges unlike those faced by optimization or evolutionary algorithms. The purpose of this chapter is to provide a foundational understanding of coevolutionary algorithms and to highlight critical theoretical and empirical work done over the last two decades. This chapter outlines the ends and means of coevolutionary algorithms: what they are meant to find, and how they should find it.

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Authors and Affiliations

  1. Icosystem Corporation, Cambridge, MA, USA

    Elena Popovici

  2. Icosystem Corporation, Cambridge, MA, USA

    Anthony Bucci

  3. Institute for Simulation and Training, University of Central Florida, Orlando, FL, USA

    R. Paul Wiegand

  4. Institute of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands

    Edwin D. De Jong

Authors
  1. Elena Popovici
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  2. Anthony Bucci
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  3. R. Paul Wiegand
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  4. Edwin D. De Jong
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Corresponding authors

Correspondence to Elena Popovici , Anthony Bucci or R. Paul Wiegand .

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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Popovici, E., Bucci, A., Wiegand, R.P., De Jong, E.D. (2012). Coevolutionary Principles. 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_31

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