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Global Expectation-Violation as Fitness Function in Evolutionary Composition

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Applications of Evolutionary Computing (EvoWorkshops 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5484))

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Abstract

Previous approaches to Common Practice Period style automated composition – such as Markov models and Context-Free Grammars (CFGs) – do not well characterise global, context-sensitive structure of musical tension and release. Using local musical expectation violation as a measure of tension, we show how global tension structure may be extracted from a source composition and used in a fitness function. We demonstrate the use of such a fitness function in an evolutionary algorithm for a highly constrained task of composition from pre-determined musical fragments. Evaluation shows an automated composition to be effectively indistinguishable from a similarly constrained composition by an experienced composer.

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Author information

Authors and Affiliations

  1. Computing Laboratory, University of Oxford, UK

    Tim Murray Browne

  2. Adaptive Behaviour Research Group, University of Sheffield, UK

    Charles Fox

Authors
  1. Tim Murray Browne
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  2. Charles Fox
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Editor information

Editors and Affiliations

  1. Department of Animal Production Epidemiology and Ecology, University of Torino, Via Leonardo da Vinci 44, 10095, Grugliasco, Italy

    Mario Giacobini

  2. Quinn School of Business, Belfield, University College Dublin, Dublin 4, Ireland

    Anthony Brabazon

  3. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  4. Dalla Molle Institute for Artificial Intelligence (IDSIA), Gallelria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  5. School of Engineering and Applied Science,Aston Triangle, Aston University, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Complex Adaptive Systems Group, Instituto Tecnológico de Informática, Ciudad PolitŽcnica de la Innovacin, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna Isabel Esparcia-Alcázar

  7. Next Generation Itelligent Networks Research Center (nexGIN RC), National University of Computer and Emerging Sciences (NUCES), Islamabad, Pakistan

    Muddassar Farooq

  8. Faculty of Economics and Social Sciences, Helmut-Schmidt-University, Holstenhofweg 85, 22043, Hamburg, Germany

    Andreas Fink

  9. Department of Informatics Engineering, Polo II - Pinhal de Marrocos, University of Coimbra, 3030 - 290, Coimbra, Portugal

    Penousal Machado

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© 2009 Springer-Verlag Berlin Heidelberg

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Browne, T.M., Fox, C. (2009). Global Expectation-Violation as Fitness Function in Evolutionary Composition. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_60

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  • DOI: https://doi.org/10.1007/978-3-642-01129-0_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01128-3

  • Online ISBN: 978-3-642-01129-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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