Introduction of Interactive Evolutionary Computation and Its Applications to CG Creativity

  • Hideyuki Takagi
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


We summarize the outline of Interactive Evolutionary Computation (IEC) and discuss its research directions. Then, we introduce four IEC-based educational systems for artistic creativity for CG beginners. They are for CG lighting design, virtual aquarium, figurative education, and fireworks animation.


Computer Graphic Psychological Distance Figurative Education Interactive Genetic Algorithm Interactive Evolutionary Computation 
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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  1. 1.
    Aoki K. Takagi H., and Fujimura N. (1996) “Interactive GA-based design support system for lighting design in computer graphics,” in Int. Conf. on Soft Computing (IIZUKA ‘86), Iizuka, Fukuoka, Japan, World Scientific, Singapore, 533–536.Google Scholar
  2. 2.
    Aoki K. and Takagi H., (1997) “3-D CG lighting with an interactive GA,” in 1st Int. Conf. on Conventional and Knowledge-based Intelligent Electronic Systems (KES’97), Adelaide, Australia, 296–301.Google Scholar
  3. 3.
    Aoki K. and Takagi H., (1998) “Interactive GA-based design support system for lighting design in 3-D computer graphics,” Trans. of IEICE, J81-DII(7), 1601–1608, (in Japanese).Google Scholar
  4. 4.
    Bézier, P. (1972) Numerical Control: Mathematics and Applications, Wiley.MATHGoogle Scholar
  5. 5.
    Dawkins, R. (1986) The Blind Watchmaker, Essex: Longman.Google Scholar
  6. 6.
    Hayashida N. and Takagi H., (2002) “Acceleration of EC Convergence with Landscape Visualization and Human Intervention,” Applied Soft Computing, Elsevier Science, (will appear).Google Scholar
  7. 7.
    Nishino H., Takagi H., Cho S. B., and Utsumiya K., (2001) “A 3D Modeling System for Creative Design,” in 15th Int. Conf. on Information Networking (ICOIN-15), Beppu, Japan, 479–486.Google Scholar
  8. 8.
    Nishino, H., Takagi, H. and Utsumiya, K., (2001) “Implementation and Evaluation of an IEC-Based 3D Modeling System,” in IEEE Int. Conf. on Systems, Man, and Cybernetics Conference (SMC2001), Tucson, AZ, USA, 1047–1052.Google Scholar
  9. 9.
    Poli A. and Cagnoni S., (1997) “Genetic programming with user-driven selection: Experiments on the evolution of algorithms for image enhancement,” in 2nd Annual Conf. on Genetic Programming, 269–277.Google Scholar
  10. 10.
    Reeves W. T., (1983) “Particle System–A Technique for Modeling a Class of Fuzzy Objects”, Computer Graphics 17(3), SIGGRAPH’83, 359–376.Google Scholar
  11. 11.
    Takagi H., (2001) “Interactive Evolutionary Computation: Fusion of the Capacities of EC Optimization and Human Evaluation,” Proceedings of the IEEE, 89 (9), 1275–1296.CrossRefGoogle Scholar
  12. 12.
    Watanabe T. and Takagi H., (1995) “Recovering system of the distorted speech using interactive genetic algorithms,” in IEEE Int. Conf. on Systems, Man and Cybernetics (SMC’95), Vancouver, Canada, 1, 684–689.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Hideyuki Takagi
    • 1
  1. 1.Kyushu Institute of DesignMinami-ku, FukuokaJapan

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