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dc.contributor.authorLones, John
dc.contributor.authorCanamero, Lola
dc.date.accessioned2014-09-29T13:30:58Z
dc.date.available2014-09-29T13:30:58Z
dc.date.issued2013-12-31
dc.identifier.citationLones , J & Canamero , L 2013 , Epigenetic adaptation through hormone modulation in autonomous robots . in 2013 IEEE 3rd Joint Int Conf on Development and Learning and Epigenetic Robotics : ICDL 2013 - Electronic Conference Proceedings . , 6652561 , IEEE , 2013 IEEE 3rd Joint International Conference on Development and Learning and Epigenetic Robotics, ICDL 2013 , Osaka , United Kingdom , 18/08/13 . https://doi.org/10.1109/DevLrn.2013.6652561
dc.identifier.citationconference
dc.identifier.isbn9781479910366
dc.identifier.otherPURE: 7602216
dc.identifier.otherPURE UUID: d6315927-c57a-460e-b273-1ed4448add49
dc.identifier.otherScopus: 84891062687
dc.identifier.urihttp://hdl.handle.net/2299/14489
dc.description.abstractEpigenetic adaptation provides biological organisms with the ability to adjust their physiology and/or morphology in order to meet some of the challenges posed by their environment. Recent research has suggested that this process may be controlled by hormones. In this paper, we present a model that allows an autonomous robot to develop its systems in accordance with the environment it is currently situated in. Experiments have been undertaken in multiple environments with different challenges and niches to negotiate. We have so far seen encouraging results and the emergence of unique behaviours tailored to exploiting its current environment.en
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartof2013 IEEE 3rd Joint Int Conf on Development and Learning and Epigenetic Robotics
dc.subjectArtificial Intelligence
dc.subjectHuman-Computer Interaction
dc.subjectSoftware
dc.titleEpigenetic adaptation through hormone modulation in autonomous robotsen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionAdaptive Systems
dc.relation.schoolSchool of Computer Science
dcterms.dateAccepted2013-12-31
rioxxterms.versionofrecordhttps://doi.org/10.1109/DevLrn.2013.6652561
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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