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A New Fitness Function for Evolutionary Music Composition

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Mathematics and Computation in Music (MCM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13267))

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Abstract

In this paper we propose a new fitness function for Evolutionary Computation purposes, based on a weighted by neighborhood average distance between two sequences of points within any metric space. We will apply this fitness function to the field of Computer-Assisted Composition focusing on the problem of thematic bridging, consisting in the evolutionary creation of a soft set of transitions between two given different melodies, the initial and the final one. Several self-adaptive strategies will be used to perform the search. A symbolic melody will be genotypically mapped into a sequence of genes, each of then containing the information of duration, frequency and time distance to following note. We will test the implementation of the fitness function by means of two experiments, showing some of the intermediate melodies generated in a successful run, and benchmarking every experiment with performance indicators for any of the three distinct evolutionary strategies implemented. The results prove this novel fitness function to be a quick and suitable way for individual evaluation in genetic algorithms.

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Authors and Affiliations

  1. International University of La Rioja (UNIR), Logroño, La Rioja, Spain

    Brian Martínez-Rodríguez

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  1. Brian Martínez-Rodríguez
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Correspondence to Brian Martínez-Rodríguez .

Editor information

Editors and Affiliations

  1. Georgia State University, Atlanta, GA, USA

    Mariana Montiel

  2. Technological University of the Mixteca, Huajuapan de León, Mexico

    Octavio A. Agustín-Aquino

  3. Universidad Politécnica de Madrid, Madrid, Spain

    Francisco Gómez

  4. Life University, Marietta, GA, USA

    Jeremy Kastine

  5. National Autonomous University of Mexico, Mexico City, Distrito Federal, Mexico

    Emilio Lluis-Puebla

  6. Georgia State University, Atlanta, GA, USA

    Brent Milam

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Martínez-Rodríguez, B. (2022). A New Fitness Function for Evolutionary Music Composition. In: Montiel, M., Agustín-Aquino, O.A., Gómez, F., Kastine, J., Lluis-Puebla, E., Milam, B. (eds) Mathematics and Computation in Music. MCM 2022. Lecture Notes in Computer Science(), vol 13267. Springer, Cham. https://doi.org/10.1007/978-3-031-07015-0_17

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  • DOI: https://doi.org/10.1007/978-3-031-07015-0_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-07014-3

  • Online ISBN: 978-3-031-07015-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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