Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition

Michael Mcloughlin; Simon Ingram; Luke Edward Rendell; Luca Ubaldo Lamoni; Alexis Kirke; Ellen Clare Garland; Michael Noad; Eduardo Miranda

Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition

Michael Mcloughlin, Simon Ingram, Luke Edward Rendell, Luca Ubaldo Lamoni, Alexis Kirke, Ellen Clare Garland, Michael Noad, Eduardo Miranda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Humpback whales (Megaptera Novaengliae) present one of the most complex displays of cultural transmission amongst non-humans. During breeding seasons, male humpback whales create long, hierarchical songs, which are shared amongst a population. Every male in the population conforms to the same song in a population. During the breeding season these songs slowly change and the song at the end of the breeding season is significantly different from the song heard at the start of the breeding season. The song of a population can also be replaced, if a new song from a different population is introduced.This is known as song revolution. Our research focuses on building computational multi agent models, which seek to recreate these phenomena observed in the wild.Our research relies on methods inspired by computational multi agent models for the evolution of music. This interdisciplinary approach has allowed us to adapt our model so that it may be used not only as a scientific tool, but also a creative tool for algorithmic composition. This paper discusses the model in detail, and then demonstrates how it may be adapted for use as an algorithmic composition tool.

Original language	English
Title of host publication	Proceedings SMC 2016
Editors	Rolf Großmann, Georg Hajdu
Publisher	Hochschule für Musik und Theater Hamburg
Pages	274-280
ISBN (Print)	9783000537004
Publication status	Published - 31 Aug 2016
Event	13th Sound and Music Computing Conference and Summer School - Finkenau Campus, University of Applied Sciences (HAW), Hamburg, Germany Duration: 31 Aug 2016 → 3 Sept 2016 Conference number: 13 http://quintetnet.hfmt-hamburg.de/SMC2016/

Publication series

Name	Proceedings of the SMC Conferences
ISSN (Electronic)	2518-3672

Conference

Conference	13th Sound and Music Computing Conference and Summer School
Abbreviated title	SMC 2016
Country/Territory	Germany
City	Hamburg
Period	31/08/16 → 3/09/16
Internet address	http://quintetnet.hfmt-hamburg.de/SMC2016/

Access to Document

SMC2016_Mclouglin_final
Copyright: © 2016 First author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Final published version, 1.11 MBLicence: CC BY

Cite this

Mcloughlin, M., Ingram, S., Rendell, L. E., Lamoni, L. U., Kirke, A., Garland, E. C., Noad, M., & Miranda, E. (2016). Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition. In R. Großmann, & G. Hajdu (Eds.), Proceedings SMC 2016 (pp. 274-280). (Proceedings of the SMC Conferences). Hochschule für Musik und Theater Hamburg.

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title = "Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition",

abstract = "Humpback whales (Megaptera Novaengliae) present one of the most complex displays of cultural transmission amongst non-humans. During breeding seasons, male humpback whales create long, hierarchical songs, which are shared amongst a population. Every male in the population conforms to the same song in a population. During the breeding season these songs slowly change and the song at the end of the breeding season is significantly different from the song heard at the start of the breeding season. The song of a population can also be replaced, if a new song from a different population is introduced.This is known as song revolution. Our research focuses on building computational multi agent models, which seek to recreate these phenomena observed in the wild.Our research relies on methods inspired by computational multi agent models for the evolution of music. This interdisciplinary approach has allowed us to adapt our model so that it may be used not only as a scientific tool, but also a creative tool for algorithmic composition. This paper discusses the model in detail, and then demonstrates how it may be adapted for use as an algorithmic composition tool. ",

author = "Michael Mcloughlin and Simon Ingram and Rendell, {Luke Edward} and Lamoni, {Luca Ubaldo} and Alexis Kirke and Garland, {Ellen Clare} and Michael Noad and Eduardo Miranda",

year = "2016",

month = aug,

day = "31",

language = "English",

isbn = "9783000537004",

series = "Proceedings of the SMC Conferences",

publisher = "Hochschule f{\"u}r Musik und Theater Hamburg",

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booktitle = "Proceedings SMC 2016",

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url = "http://quintetnet.hfmt-hamburg.de/SMC2016/",

}

Mcloughlin, M, Ingram, S, Rendell, LE, Lamoni, LU, Kirke, A, Garland, EC, Noad, M & Miranda, E 2016, Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition. in R Großmann & G Hajdu (eds), Proceedings SMC 2016. Proceedings of the SMC Conferences, Hochschule für Musik und Theater Hamburg, pp. 274-280, 13th Sound and Music Computing Conference and Summer School, Hamburg, Germany, 31/08/16.

Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition. / Mcloughlin, Michael; Ingram, Simon; Rendell, Luke Edward et al.
Proceedings SMC 2016. ed. / Rolf Großmann; Georg Hajdu. Hochschule für Musik und Theater Hamburg, 2016. p. 274-280 (Proceedings of the SMC Conferences).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Ingram, Simon

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AU - Lamoni, Luca Ubaldo

AU - Kirke, Alexis

AU - Garland, Ellen Clare

AU - Noad, Michael

AU - Miranda, Eduardo

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AB - Humpback whales (Megaptera Novaengliae) present one of the most complex displays of cultural transmission amongst non-humans. During breeding seasons, male humpback whales create long, hierarchical songs, which are shared amongst a population. Every male in the population conforms to the same song in a population. During the breeding season these songs slowly change and the song at the end of the breeding season is significantly different from the song heard at the start of the breeding season. The song of a population can also be replaced, if a new song from a different population is introduced.This is known as song revolution. Our research focuses on building computational multi agent models, which seek to recreate these phenomena observed in the wild.Our research relies on methods inspired by computational multi agent models for the evolution of music. This interdisciplinary approach has allowed us to adapt our model so that it may be used not only as a scientific tool, but also a creative tool for algorithmic composition. This paper discusses the model in detail, and then demonstrates how it may be adapted for use as an algorithmic composition tool.

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M3 - Conference contribution

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BT - Proceedings SMC 2016

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Y2 - 31 August 2016 through 3 September 2016

ER -

Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition

Abstract

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Conference

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Leverhulme Trust: Developing a data-driven multi-agent model for studying humpback whale song

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Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition

Abstract

Publication series

Conference

Access to Document

Other files and links

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Leverhulme Trust: Developing a data-driven multi-agent model for studying humpback whale song

Cite this