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dc.contributor.authorPozdniakov, Ken
dc.contributor.authorAlonso, Een
dc.contributor.authorStankovic, Ven
dc.contributor.authorTam, Ken
dc.contributor.authorJones, Ken
dc.date.accessioned2020-05-20T10:10:01Z
dc.date.issued2020-06-15en
dc.identifier.urihttp://hdl.handle.net/10026.1/15693
dc.descriptionNo embargo requireden
dc.language.isoenen
dc.titleSmart Security Audit: Reinforcement Learning with a Deep Neural Network Approximatoren
dc.typeConference Contribution
plymouth.conference-nameIEEE Cyber Scienceen
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2020-04-16en
dc.rights.embargodate2020-05-21en
dc.rights.embargoperiodNot knownen
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2020-06-15en
rioxxterms.typeConference Paper/Proceeding/Abstracten


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