Primal-improv: Towards co-evolutionary musical improvisation

Marco Scirea, Peter Eklund, Julian Togelius, Sebastian Risi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper describes a work in progress on co-evolving Artificial Neural Networks (ANNs) for music improvisation. Using this neuro-evolutionary approach the ANNs adapt to the changes in the human player's music as input, while still maintaining some of the structure of the musical piece previously evolved. The system is called Primal-Improv and evolves modules that are composed of two ANNs, one controlling pitch and one controlling rhythm. The results of a quantitative study show that, by only introducing simple rules as fitness functions, the system is able to generate more interesting arrangements than ANNs evolved without a specific objective. The emerging and interesting musical patterns that are produced by the evolved ANNs hint at the promising potential of the system.

    Original languageEnglish (US)
    Title of host publication2017 9th Computer Science and Electronic Engineering Conference, CEEC 2017 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages172-177
    Number of pages6
    ISBN (Electronic)9781538630075
    DOIs
    StatePublished - Nov 8 2017
    Event9th Computer Science and Electronic Engineering Conference, CEEC 2017 - Colchester, United Kingdom
    Duration: Sep 27 2017Sep 29 2017

    Publication series

    Name2017 9th Computer Science and Electronic Engineering Conference, CEEC 2017 - Proceedings

    Other

    Other9th Computer Science and Electronic Engineering Conference, CEEC 2017
    Country/TerritoryUnited Kingdom
    CityColchester
    Period9/27/179/29/17

    ASJC Scopus subject areas

    • Computer Science (miscellaneous)
    • Computer Networks and Communications
    • Computer Science Applications
    • Electrical and Electronic Engineering

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