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Keeping the Diversity with Small Populations Using Logic-Based Genetic Programming

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Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3103))

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Abstract

We present a new method of Logic-Based Genetic Programming (LBGP). Using the intrinsic mechanism of backtracking in Prolog, we utilize large individual programs with redundant clauses, and apply them to small populations. Our method is validated by the experiments about Symbolic Regression, and XOR problems.

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References

  1. Goldberg, D.E., Korb, B., Deb, K.: Messy Genetic Algorithms: Motivation, Analysis, and First Results. Complex Systems 3, 493–530 (1989)

    MATH  MathSciNet  Google Scholar 

  2. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)

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  3. Raik, S.: Genetic Programming in Prolog, CMU-AI-Reposiroty (1993)

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  4. Terao, M., Iba, H.: Controlling Effective Introns for Multi-Agent Learning by Genetic Programming. In: Proc. of GECCO 2000, pp. 419–426 (2000)

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Author information

Authors and Affiliations

  1. Graduate School of Business Sciences, University of Tsukuba, 3-29-1, Otsuka, Bunkyo-ku, Tokyo, 112-0012, Japan

    Ken Taniguchi & Takao Terano

Authors
  1. Ken Taniguchi
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  2. Takao Terano
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Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), Kanpur, 208016, Uttar Pradesh, India

    Kalyanmoy Deb

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© 2004 Springer-Verlag Berlin Heidelberg

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Taniguchi, K., Terano, T. (2004). Keeping the Diversity with Small Populations Using Logic-Based Genetic Programming. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_87

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  • DOI: https://doi.org/10.1007/978-3-540-24855-2_87

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22343-6

  • Online ISBN: 978-3-540-24855-2

  • eBook Packages: Springer Book Archive

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