Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition
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...
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Hochschule für Musik und Theater Hamburg
2016
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Online Access: | https://risweb.st-andrews.ac.uk/portal/en/researchoutput/adapting-a-computational-multi-agent-model-for-humpback-whale-song-research-for-use-as-a-tool-for-algorithmic-composition(66f77a04-6920-4c73-b465-1140aa421e93).html https://research-repository.st-andrews.ac.uk/bitstream/10023/9795/1/SMC2016_Mclouglin_final.pdf http://quintetnet.hfmt-hamburg.de/SMC2016/wp-content/uploads/2016/09/SMC2016_proceedings_final.pdf |
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ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/66f77a04-6920-4c73-b465-1140aa421e93 2023-05-15T16:36:03+02:00 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 Lamoni, Luca Ubaldo Kirke, Alexis Garland, Ellen Clare Noad, Michael Miranda, Eduardo Großmann, Rolf Hajdu, Georg 2016-08-31 application/pdf https://risweb.st-andrews.ac.uk/portal/en/researchoutput/adapting-a-computational-multi-agent-model-for-humpback-whale-song-research-for-use-as-a-tool-for-algorithmic-composition(66f77a04-6920-4c73-b465-1140aa421e93).html https://research-repository.st-andrews.ac.uk/bitstream/10023/9795/1/SMC2016_Mclouglin_final.pdf http://quintetnet.hfmt-hamburg.de/SMC2016/wp-content/uploads/2016/09/SMC2016_proceedings_final.pdf eng eng Hochschule für Musik und Theater Hamburg info:eu-repo/semantics/openAccess 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 . 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 . contributionToPeriodical 2016 ftunstandrewcris 2021-12-26T14:29:29Z 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. Other Non-Article Part of Journal/Newspaper Humpback Whale University of St Andrews: Research Portal |
institution |
Open Polar |
collection |
University of St Andrews: Research Portal |
op_collection_id |
ftunstandrewcris |
language |
English |
description |
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. |
author2 |
Großmann, Rolf Hajdu, Georg |
format |
Other Non-Article Part of Journal/Newspaper |
author |
Mcloughlin, Michael Ingram, Simon Rendell, Luke Edward Lamoni, Luca Ubaldo Kirke, Alexis Garland, Ellen Clare Noad, Michael Miranda, Eduardo |
spellingShingle |
Mcloughlin, Michael Ingram, Simon Rendell, Luke Edward Lamoni, Luca Ubaldo Kirke, Alexis Garland, Ellen Clare Noad, Michael Miranda, Eduardo Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition |
author_facet |
Mcloughlin, Michael Ingram, Simon Rendell, Luke Edward Lamoni, Luca Ubaldo Kirke, Alexis Garland, Ellen Clare Noad, Michael Miranda, Eduardo |
author_sort |
Mcloughlin, Michael |
title |
Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition |
title_short |
Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition |
title_full |
Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition |
title_fullStr |
Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition |
title_full_unstemmed |
Adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition |
title_sort |
adapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic composition |
publisher |
Hochschule für Musik und Theater Hamburg |
publishDate |
2016 |
url |
https://risweb.st-andrews.ac.uk/portal/en/researchoutput/adapting-a-computational-multi-agent-model-for-humpback-whale-song-research-for-use-as-a-tool-for-algorithmic-composition(66f77a04-6920-4c73-b465-1140aa421e93).html https://research-repository.st-andrews.ac.uk/bitstream/10023/9795/1/SMC2016_Mclouglin_final.pdf http://quintetnet.hfmt-hamburg.de/SMC2016/wp-content/uploads/2016/09/SMC2016_proceedings_final.pdf |
genre |
Humpback Whale |
genre_facet |
Humpback Whale |
op_source |
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 . 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 . |
op_rights |
info:eu-repo/semantics/openAccess |
_version_ |
1766026353457496064 |