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Developing Fitness Functions for Pleasant Music: Zipf’s Law and Interactive Evolution Systems

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 3449)


In domains such as music and visual art, where the quality of an individual often depends on subjective or hard to express concepts, the automating fitness assignment becomes a difficult problem. This paper discusses the application of Zipf’s Law in evaluation of music pleasantness. Preliminary results indicate that a set of Zipf-based metrics can be effectively used to classify music according to pleasantness as reported by human subjects. These studies suggest that metrics based on Zipf’s law may capture essential aspects of proportion in music as it relates to music aesthetics. We discuss the significance of these results for the automation of fitness assignment in evolutionary music systems.


  • Average Success Rate
  • Style Identification
  • Interactive Evolution
  • Fitness Assignment
  • Music Excerpt

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© 2005 Springer-Verlag Berlin Heidelberg

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Manaris, B., Machado, P., McCauley, C., Romero, J., Krehbiel, D. (2005). Developing Fitness Functions for Pleasant Music: Zipf’s Law and Interactive Evolution Systems. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25396-9

  • Online ISBN: 978-3-540-32003-6

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