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Enhancing Competitive Island Cooperative Neuro-Evolution Through Backpropagation for Pattern Classification

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Neural Information Processing (ICONIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9489))

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Abstract

Cooperative coevolution is a promising method for training neural networks which is also known as cooperative neuro-evolution. Cooperative neuro-evolution has been used for pattern classification, time series prediction and global optimisation problems. In the past, competitive island based cooperative coevolution has been proposed that employed different instances of problem decomposition methods for competition. Neuro-evolution has limitations in terms of training time although they are known as global search methods. Backpropagation algorithm employs gradient descent which helps in faster convergence which is needed for neuro-evolution. Backpropagation suffers from premature convergence and its combination with neuro-evolution can help eliminate the weakness of both the approaches. In this paper, we propose a competitive island cooperative neuro-evolutionary method that takes advantage of the strengths of gradient descent and neuro-evolution. We use feedforward neural networks on benchmark pattern classification problems to evaluate the performance of the proposed algorithm. The results show improved performance when compared to related methods.

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Notes

  1. 1.

    Keys for Tables 2 and 3

    \(\mathbf {\bar{x}}\) ev = Mean Fitness Evaluations, \(\mathbf {\bar{x}}\) er = Mean Generalisation Performance, (H) = No. Hidden Neurons, and (sr) = Success Rate

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Author information

Authors and Affiliations

  1. School of Computing Information and Mathematical Sciences, University of South Pacific, Suva, Fiji

    Gary Wong & Rohitash Chandra

  2. Artificial Intelligence and Cybernetics Research Group, Software Foundation, Nausori, Fiji

    Gary Wong & Rohitash Chandra

Authors
  1. Gary Wong
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  2. Rohitash Chandra
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Corresponding author

Correspondence to Rohitash Chandra .

Editor information

Editors and Affiliations

  1. University of Istanbul, Istanbul, Turkey

    Sabri Arik

  2. University at Qatar, Doha, Qatar

    Tingwen Huang

  3. Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia

    Weng Kin Lai

  4. University of Science Technology, Wuhan, China

    Qingshan Liu

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Wong, G., Chandra, R. (2015). Enhancing Competitive Island Cooperative Neuro-Evolution Through Backpropagation for Pattern Classification. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9489. Springer, Cham. https://doi.org/10.1007/978-3-319-26532-2_32

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  • DOI: https://doi.org/10.1007/978-3-319-26532-2_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26531-5

  • Online ISBN: 978-3-319-26532-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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