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dc.contributor.authorMcloughlin, Michael
dc.contributor.authorIngram, Simon
dc.contributor.authorRendell, Luke Edward
dc.contributor.authorLamoni, Luca Ubaldo
dc.contributor.authorKirke, Alexis
dc.contributor.authorGarland, Ellen Clare
dc.contributor.authorNoad, Michael
dc.contributor.authorMiranda, Eduardo
dc.contributor.editorGroßmann, Rolf
dc.contributor.editorHajdu, Georg
dc.identifier.citationMcloughlin , 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 .en
dc.identifier.otherORCID: /0000-0002-8240-1267/work/49580210
dc.identifier.otherORCID: /0000-0002-1121-9142/work/28052346
dc.description.abstractHumpback 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.
dc.publisherHochschule für Musik und Theater Hamburg
dc.relation.ispartofProceedings SMC 2016en
dc.relation.ispartofseriesProceedings of the SMC Conferencesen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQH301 Biologyen
dc.titleAdapting a computational multi agent model for humpback whale song research for use as a tool for algorithmic compositionen
dc.typeConference itemen
dc.contributor.sponsorThe Leverhulme Trusten
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Centre for Social Learning & Cognitive Evolutionen
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Bioacoustics groupen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen

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