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Adaptive Critics for Evolutionary Artists

  • Penousal Machado
  • Juan Romero
  • María Luisa Santos
  • Amílcar Cardoso
  • Bill Manaris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3005)

Abstract

We focus on the development of artificial art critics. These systems analyze artworks, extracting relevant features, and produce an evaluation of the perceived pieces. The ability to perform aesthetic judgments is a desirable characteristic in an evolutionary artificial artist. As such, the inclusion of artificial art critics in these systems may improve their artistic abilities. We propose artificial art critics for the domains of music and visual arts, presenting a comprehensive set of experiments in author identification tasks. The experimental results show the viability and potential of our approach.

Keywords

Feature Extractor Aesthetic Judgment Musical Score Zipf Distribution Evolutionary Artist 
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 2004

Authors and Affiliations

  • Penousal Machado
    • 1
  • Juan Romero
    • 2
  • María Luisa Santos
    • 2
  • Amílcar Cardoso
    • 1
  • Bill Manaris
    • 3
  1. 1.Centre for Informatics and Systems of the University of CoimbraCoimbraPortugal
  2. 2.Creative Computer Line, RNASA Lab. Faculty of Computer ScienceUniversity of CoruñaSpain
  3. 3.Computer Science DepartmentCollege of CharlestonCharlestonUSA

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