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Eco-Grammar Systems as Models for Parallel Evolutionary Algorithms

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Stochastic Algorithms: Foundations and Applications (SAGA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3777))

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Abstract

Evolutionary Algorithms (EAs), biological inspired searching techniques, represent a research domain where theoretical proofs are still missing. Due to the lack of theoretical foundations, an extensive experimental work developed many variations of the basic model. Remarkable tendencies such as variable control parameters or parallel populations try to overcome the stagnation observed at the end of evolutions.

We tried to study from theoretical point of view the possibility of modelling parallel EAs using Eco-grammar systems. We expect that our research opens a new perspective over EAs behavior and our framework can bring theoretical results that will lead to new recommendations for EAs architectures as well as for specific details requested by practical problems.

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Author information

Authors and Affiliations

  1. Research Group on Mathematical Linguistics, Rovira i Virgili University, Pl. Imperial Tárraco 1, 43005, Tarragona, Spain

    Adrian Horia Dediu & María Adela Grando

Authors
  1. Adrian Horia Dediu
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  2. María Adela Grando
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Editor information

Editors and Affiliations

  1. Department of Discrete Mathematics, Leninskie Gory, Moscow State University, 119992, Moscow, Russia

    Oleg B. Lupanov  & Oktay M. Kasim-Zade  & 

  2. Faculty of Mechanics and Mathematics, Department of Discrete Mathematics, Leninskie Gory, Moscow State University, 119992, Moscow, Russia

    Alexander V. Chaskin

  3. Department of Computer Science, King’s College London, WC2R 2LS, London, UK

    Kathleen Steinhöfel

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© 2005 Springer-Verlag Berlin Heidelberg

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Dediu, A.H., Grando, M.A. (2005). Eco-Grammar Systems as Models for Parallel Evolutionary Algorithms. In: Lupanov, O.B., Kasim-Zade, O.M., Chaskin, A.V., Steinhöfel, K. (eds) Stochastic Algorithms: Foundations and Applications. SAGA 2005. Lecture Notes in Computer Science, vol 3777. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11571155_19

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  • DOI: https://doi.org/10.1007/11571155_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29498-6

  • Online ISBN: 978-3-540-32245-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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