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Decision-making in brains and robots - the case for an interdisciplinary approach

cam.issuedOnline2019-02-05
cam.orpheus.successThu Jan 30 10:52:07 GMT 2020 - Embargo updated
dc.contributor.authorSeymour, Benjamin
dc.contributor.authorLee, Sang Wan
dc.contributor.orcidSeymour, Benjamin [0000-0003-1724-5832]
dc.date.accessioned2019-02-12T00:33:21Z
dc.date.available2019-02-12T00:33:21Z
dc.date.issued2019
dc.description.abstractReinforcement Learning describes a general method for trial-and-error learning, and has emerged as a dominant framework both for optimal control in autonomous robots, and understanding decision-making in the brain. Despite their common roots, however, these two fields have evolved largely independently. In this perspective we consider how each now face problems that could potentially be addressed by insights from the other, and argue that an interdisciplinary approach could greatly accelerate progress in both.
dc.identifier.doi10.17863/CAM.36527
dc.identifier.eissn2352-1546
dc.identifier.issn2352-1546
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/289265
dc.language.isoeng
dc.publisherElsevier Limited
dc.publisher.urlhttps://www.sciencedirect.com/science/article/pii/S2352154618302067
dc.subject5202 Biological Psychology
dc.subject32 Biomedical and Clinical Sciences
dc.subject3209 Neurosciences
dc.subject52 Psychology
dc.subjectNeurosciences
dc.subjectMental health
dc.titleDecision-making in brains and robots - the case for an interdisciplinary approach
dc.typeArticle
dcterms.dateAccepted2018-12-22
prism.endingPage145
prism.publicationNameCurrent Opinion in Behavioral Sciences
prism.startingPage137
prism.volume26
pubs.funder-project-idWellcome Trust (097490/Z/11/Z)
pubs.funder-project-idArthritis Research UK (21192)
pubs.funder-project-idArthritis Research UK (21537)
rioxxterms.licenseref.startdate2018-12-22
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
rioxxterms.typeJournal Article/Review
rioxxterms.versionAM
rioxxterms.versionofrecord10.1016/j.cobeha.2018.12.012

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