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Estimation of Distribution Algorithms with Graph Kernels for Graphs with Node Types

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Intelligent and Evolutionary Systems

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 8))

Abstract

We have proposed a novel Estimation of Distribution Algorithms with graph kernels (EDA-GK). By using the graph kernels, we can search for solutions in a feature space. The use of the graph kernel can eliminate the effect of the ruggedness of genotype-phenotype mappings of evolutionary algorithms. In this paper, we extend the EDA-GK to cope with graphs with node types. In order to achieve this, the histogram in the kernel density estimation function is separated into several sub-histograms for modes of inter-types, and for nodes of each type. Experimental results on the Edge-Max problems show the effectiveness of the proposed method.

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Notes

  1. 1.

    For the extended version of the EDA-GK, i.e., the proposed method in this paper, Eq. (5) is used for the calculation of the function f in Eq. (3).

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Acknowledgments

This work was partially supported by the Grant-in-Aid for Young Scientists (B) and the Grant-in-Aid for Scientific Research (C) of MEXT, Japan (23700267, 26330291).

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Authors and Affiliations

  1. Kindai University, Higashi-Osaka, Japan

    Kenta Maezawa & Hisashi Handa

Authors
  1. Kenta Maezawa
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  2. Hisashi Handa
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Corresponding author

Correspondence to Hisashi Handa .

Editor information

Editors and Affiliations

  1. School of Engineering and Information Technology, Australian Defence Force Academy, The University of New South Wales, Canberra, Australian Capital Territory, Australia

    George Leu

  2. School of Engineering and Information Technology, Australian Defence Force Academy, The University of New South Wales, Canberra, Australian Capital Territory, Australia

    Hemant Kumar Singh

  3. School of Engineering and Information Technology, Australian Defence Force Academy, The University of New South Wales, Canberra, Australian Capital Territory, Australia

    Saber Elsayed

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Maezawa, K., Handa, H. (2017). Estimation of Distribution Algorithms with Graph Kernels for Graphs with Node Types. In: Leu, G., Singh, H., Elsayed, S. (eds) Intelligent and Evolutionary Systems. Proceedings in Adaptation, Learning and Optimization, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-49049-6_18

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  • DOI: https://doi.org/10.1007/978-3-319-49049-6_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49048-9

  • Online ISBN: 978-3-319-49049-6

  • eBook Packages: EngineeringEngineering (R0)

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