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Analysis of a Genetic Model with Finite Populations

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3612))

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Abstract

Simple genetic algorithms on populations of l-binary words usually become iterative systems on 2l dimensional spaces when populations have size infinite. However, in a particular model (BCCG model) previously introduced, it has been shown that the iterative system works in a l-dimensional space.

In this paper we propose a simplification of the BCCG model and we analyze it in the case of large but finite-size populations. In particular:

  1. 1

    We exhibit a Markov chain with states in ℝl that approximates the system behavior.

  2. 2

    We estimate the steady state distribution of the Markov chain.

Partially supported by the PRIN Project “Formal languages and automata: methods, models and applications”, MIUR.

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Author information

Authors and Affiliations

  1. Dipartimento di Scienze dell’Informazione, Universitá degli Studi di Milano, via Comelico, 39, 20135, Milano, Italy

    Alberto Bertoni & Paola Campadelli

  2. Dipartimento di Informatica, Universitá degli Studi di Verona, strada le Grazie, 15, 37134, Verona, Italy

    Roberto Posenato

Authors
  1. Alberto Bertoni
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  2. Paola Campadelli
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  3. Roberto Posenato
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Bertoni, A., Campadelli, P., Posenato, R. (2005). Analysis of a Genetic Model with Finite Populations. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_28

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  • DOI: https://doi.org/10.1007/11539902_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28320-1

  • Online ISBN: 978-3-540-31863-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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