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Genetic Algorithm with Knowledge-Based Encoding for Interactive Fashion Design

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 1886)

Abstract

Evolutionary computation gives a great potential in several real-world problems as a powerful tool for optimization and classification, but there still remain a lot of obstacles to be applied to artistic domains. To overcome the shortcoming a variety of techniques have been proposed, and among them interactive genetic algorithm (IGA) is extensively studied in these days. IGA exploits the interaction with human in the course of evolution by taking his evaluation as fitness. In this paper, we propose an effective knowledge-based encoding scheme for IGA in a real-world application. This method has been applied to a fashion design aid system, which can reflect user’s preference or emotion that is usually difficult to be expressed explicitly. To show that the proposed encoding scheme produces more realistic and practical design, an experimental study as well as a theoretical investigation with schema theorem has been conducted.

Keywords

  • Genetic Algorithm
  • Encode Scheme
  • Encode Method
  • Domain Specific Knowledge
  • Sequential Encode

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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© 2000 Springer-Verlag Berlin Heidelberg

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Kim, HS., Cho, SB. (2000). Genetic Algorithm with Knowledge-Based Encoding for Interactive Fashion Design. In: Mizoguchi, R., Slaney, J. (eds) PRICAI 2000 Topics in Artificial Intelligence. PRICAI 2000. Lecture Notes in Computer Science(), vol 1886. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44533-1_42

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  • DOI: https://doi.org/10.1007/3-540-44533-1_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67925-7

  • Online ISBN: 978-3-540-44533-3

  • eBook Packages: Springer Book Archive