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Primal-improv: Towards co-evolutionary musical improvisation

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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Primal-improv: Towards co-evolutionary musical improvisation. / Scirea, M.; Eklund, P.; Togelius, J.; Risi, S.

2017 9th Computer Science and Electronic Engineering (CEEC). IEEE, 2017. p. 172-177.

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Harvard

Scirea, M, Eklund, P, Togelius, J & Risi, S 2017, Primal-improv: Towards co-evolutionary musical improvisation. in 2017 9th Computer Science and Electronic Engineering (CEEC). IEEE, pp. 172-177. https://doi.org/10.1109/CEEC.2017.8101620

APA

Scirea, M., Eklund, P., Togelius, J., & Risi, S. (2017). Primal-improv: Towards co-evolutionary musical improvisation. In 2017 9th Computer Science and Electronic Engineering (CEEC) (pp. 172-177). IEEE. https://doi.org/10.1109/CEEC.2017.8101620

Vancouver

Scirea M, Eklund P, Togelius J, Risi S. Primal-improv: Towards co-evolutionary musical improvisation. In 2017 9th Computer Science and Electronic Engineering (CEEC). IEEE. 2017. p. 172-177 https://doi.org/10.1109/CEEC.2017.8101620

Author

Scirea, M. ; Eklund, P. ; Togelius, J. ; Risi, S. / Primal-improv: Towards co-evolutionary musical improvisation. 2017 9th Computer Science and Electronic Engineering (CEEC). IEEE, 2017. pp. 172-177

Bibtex

@inproceedings{8e269b6d006c4d50ac29a01adec26089,
title = "Primal-improv: Towards co-evolutionary musical improvisation",
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.",
keywords = "evolutionary computation, music, neural nets, PRIMAL-IMPROV, artificial neural networks, co-evolutionary musical improvisation, evolved ANN hint, human player, interesting musical patterns, music improvisation, neuro-evolutionary approach, Evolutionary computation, Network topology, Neural networks, Real-time systems, Rhythm, Topology",
author = "M. Scirea and P. Eklund and J. Togelius and S. Risi",
year = "2017",
month = sep
day = "1",
doi = "10.1109/CEEC.2017.8101620",
language = "English",
isbn = "978-1-5386-3007-5",
pages = "172--177",
booktitle = "2017 9th Computer Science and Electronic Engineering (CEEC)",
publisher = "IEEE",
address = "United States",

}

RIS

TY - GEN

T1 - Primal-improv: Towards co-evolutionary musical improvisation

AU - Scirea, M.

AU - Eklund, P.

AU - Togelius, J.

AU - Risi, S.

PY - 2017/9/1

Y1 - 2017/9/1

N2 - 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.

AB - 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.

KW - evolutionary computation

KW - music

KW - neural nets

KW - PRIMAL-IMPROV

KW - artificial neural networks

KW - co-evolutionary musical improvisation

KW - evolved ANN hint

KW - human player

KW - interesting musical patterns

KW - music improvisation

KW - neuro-evolutionary approach

KW - Evolutionary computation

KW - Network topology

KW - Neural networks

KW - Real-time systems

KW - Rhythm

KW - Topology

U2 - 10.1109/CEEC.2017.8101620

DO - 10.1109/CEEC.2017.8101620

M3 - Article in proceedings

SN - 978-1-5386-3007-5

SP - 172

EP - 177

BT - 2017 9th Computer Science and Electronic Engineering (CEEC)

PB - IEEE

ER -

ID: 82456763