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Natural vs. Unnatural Decomposition in Cooperative Coevolution

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Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6839))

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Abstract

Problem decomposition is the first step to apply a cooperative coevolutionary algorithm (CCEA) to a problem. This step determines how to divide the problem into components with an appropriate granularity. Most of the current methods implement a natural-based decomposition where each component plays a specific role or represents an emergent property. However, there could exist some real problems that the roles or the properties are hard to determine or somewhat unclear. This paper offers a solution by decomposing the problems in an unnatural way, which implements a blind decomposition. Our primary analysis indicates that the blind decomposition is feasible. We also provide some basic advice on how to implement the blind decomposition in combination with different collaboration methods.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Science, Norwegian University of Science and Technology, Norway

    Min Shi

Authors
  1. Min Shi
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  4. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    M. Michael Gromiha

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Shi, M. (2012). Natural vs. Unnatural Decomposition in Cooperative Coevolution. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_18

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  • DOI: https://doi.org/10.1007/978-3-642-25944-9_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25943-2

  • Online ISBN: 978-3-642-25944-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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