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Genetic Algorithms for Optimization of Boids Model

  • Yen-Wei Chen
  • Kanami Kobayashi
  • Xinyin Huang
  • Zensho Nakao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)

Abstract

In this paper, we present an extended boids model for simulating the aggregate moving of fish schools in a complex environment. Three behavior rules are added to the extended boids model: following a feed; avoiding obstacle; avoiding enemy boids. The moving vector is a linear combination of every behavior rule vector, and the coefficients should be optimized. We also proposed a genetic algorithm to optimize the coefficients. Experimental results show that by using the GA-based optimization, the aggregate motions of fish schools become more realistic and similar to behaviors of real fish world.

Keywords

Genetic Algorithm Complex Environment Fish School American Fishery Society Blind Deconvolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yen-Wei Chen
    • 1
    • 2
  • Kanami Kobayashi
    • 1
  • Xinyin Huang
    • 3
  • Zensho Nakao
    • 4
  1. 1.School of Information Science and Eng.Ristumeikan Univ.ShigaJapan
  2. 2.College of Elect. and Information Eng.Central South Forest Univ.ChangshaChina
  3. 3.School of EducationSoochow UniversitySuzhouChina
  4. 4.Faculy of Eng.Univ. of the RyukyusOkinawaJapan

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