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Evolving Structure in Liquid Music

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The Art of Artificial Evolution

Part of the book series: Natural Computing Series ((NCS))

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Summary

A software application called “Musical Gene Pool” is described. It was designed to evolve non-linear music from an initial random soup of sounds, which play continuously. Most evolutionary music systems to date require the user to select for musical aspects in a piecemeal fashion, whereas this system is experienced as continuous music throughout the entire process, as follows: a human listener gives fitness rewards after sounds (organisms) emerge from the gene pool, take turns playing, and return back to the pool. Organisms start out unicellular (one sound), but as the listener selectively rewards random sequences deemed more musical than others, some organisms join up to form larger, multicellular organisms – which become phrases or extended musical gestures. Genetic operators of splitting, death, replication, and mutation occur in the gene pool among rewarded organisms. This results in gradual evolution of structure as the music continues to play. This emerges in response to the listener’s own internal emerging musical language, based on accumulated musical memory. This structure is liquid – continually able to flow and rearrange to allow serendipity. While there is a limit to organism length (duration of phrases), it is proposed that the interactive scheme could be adjusted to evolve increasingly larger organisms, and hence, longer musical passages. These would essentially be mobile chunks of linear music with self-similarity in their structures – revealing the histories of their evolution.

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© 2008 Springer-Verlag Berlin Heidelberg

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Ventrella, J.J. (2008). Evolving Structure in Liquid Music. In: Romero, J., Machado, P. (eds) The Art of Artificial Evolution. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72877-1_13

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  • DOI: https://doi.org/10.1007/978-3-540-72877-1_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72876-4

  • Online ISBN: 978-3-540-72877-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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