Collective behaviour across animal species

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dc.contributorVirginia Techen
dc.contributor.authorDeLellis, P.en
dc.contributor.authorPolverino, G.en
dc.contributor.authorUstuner, G.en
dc.contributor.authorAbaid, Nicoleen
dc.contributor.authorMacri, S.en
dc.contributor.authorBollt, Erik M.en
dc.contributor.authorPorfiri, M.en
dc.contributor.departmentBiomedical Engineering and Mechanicsen
dc.date.accessed2014-06-13en
dc.date.accessioned2014-06-16T14:11:24Zen
dc.date.available2014-06-16T14:11:24Zen
dc.date.issued2014-01-01en
dc.description.abstractWe posit a new geometric perspective to define, detect, and classify inherent patterns of collective behaviour across a variety of animal species. We show that machine learning techniques, and specifically the isometric mapping algorithm, allow the identification and interpretation of different types of collective behaviour in five social animal species. These results offer a first glimpse at the transformative potential of machine learning for ethology, similar to its impact on robotics, where it enabled robots to recognize objects and navigate the environment.en
dc.description.sponsorshipNational Science Foundation CMMI-1129820, CMMI-1129859, CMMI-0745753en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationDeLellis, P.; Polverino, G.; Ustuner, G.; Abaid, N.; Macri, S.; Bollt, E. M.; Porfiri, M., "Collective behaviour across animal species," Scientific Reports 4:3723, (2014). DOI: 10.1038/srep03723.en
dc.identifier.doihttps://doi.org/10.1038/srep03723en
dc.identifier.issn2045-2322en
dc.identifier.urihttp://hdl.handle.net/10919/48931en
dc.identifier.urlhttp://www.nature.com/srep/2014/140116/srep03723/full/srep03723.htmlen
dc.language.isoen_USen
dc.publisherNature Publishing Groupen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNonlinear dimensionality reductionen
dc.subjectXenopus-laevisen
dc.subjectZebrafishen
dc.subjectMotionen
dc.subjectMultidisciplinary sciencesen
dc.titleCollective behaviour across animal speciesen
dc.title.serialScientific Reportsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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