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Genetic algorithms in evolutionary modelling

  • Chris Birchenhall

    (School of Economic Studies, PREST and CRIC, University of Manchester, Oxford Road, Manchester M13 9PL, UK)

  • Nikos Kastrinos

    (School of Economic Studies, PREST and CRIC, University of Manchester, Oxford Road, Manchester M13 9PL, UK)

  • Stan Metcalfe

    (School of Economic Studies, PREST and CRIC, University of Manchester, Oxford Road, Manchester M13 9PL, UK)

Evolutionary modellers have recently taken an interest in the use of computer simulations based on genetic algorithms; this paper offers two contributions to this literature. In the initial sections we aim to place the GA into a general review of evolutionary dynamics, including Fisher's Principle. In the second half of the paper, we offer a modified GA that replaces the selection and crossover operators with a selective transfer operator. We argue this modified algorithm has a ready interpretation in the modelling of learning, namely as a proxy for imitation in a population working with modular technologies. A simple application is used to give an initial assessment of the algorithm and to test Fisher's Principle.

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Article provided by Springer in its journal Journal of Evolutionary Economics.

Volume (Year): 7 (1997)
Issue (Month): 4 ()
Pages: 375-393

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Handle: RePEc:spr:joevec:v:7:y:1997:i:4:p:375-393
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