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Selection Enthusiasm

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Simulated Evolution and Learning (SEAL 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4247))

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Abstract

Selection Enthusiasm is a technique that allows weaker individuals in a population to compete with stronger individuals. In essence, each time a individual is selected its enthusiasm for being selected again is diminished relatively; the converse happens to the unselected individuals i.e. their raw fitness is adjusted. Therefore the fitness of an individual is based on two parameters; objectiveness and Selected Enthusiasm. The effects of such a technique are measured and results show that using selection enthusiasism yields fitter individuals and a more diverse population.

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Author information

Authors and Affiliations

  1. Middlesex University, UK

    A. Agrawal & I. Mitchell

Authors
  1. A. Agrawal
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  2. I. Mitchell
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Editor information

Editors and Affiliations

  1. Department of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung County Taiwan, ROC

    Tzai-Der Wang

  2. School of Computer Science and information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Xiaodong Li

  3. AI-ECON Research Center, Department of Economics, National Chengchi University, 11623, Taipei, Taiwan

    Shu-Heng Chen

  4. Department of Computer Science and Technology, University of Sci. & Tech. of China, 230026, Hefei, Anhui, P.R. China

    Xufa Wang

  5. School of Information Technology and Electrical Engineering, University of New South Wales, Australian Defence Force Academy, Canberra, Australia

    Hussein Abbass

  6. The Univertity of Tokyo, Japan

    Hitoshi Iba

  7. Department of Computer, University of Science and Technology of China, 230027, Hefei, China

    Guo-Liang Chen

  8. University of Birmingham, Birmingham, UK

    Xin Yao

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© 2006 Springer-Verlag Berlin Heidelberg

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Agrawal, A., Mitchell, I. (2006). Selection Enthusiasm. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_57

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  • DOI: https://doi.org/10.1007/11903697_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47331-2

  • Online ISBN: 978-3-540-47332-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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