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dc.contributor.authorTurner, Matthew
dc.contributor.authorHemberg, Erik
dc.contributor.authorO'Reilly, Una-May
dc.date.accessioned2022-11-04T17:53:38Z
dc.date.available2022-11-04T17:53:38Z
dc.date.issued2022-07-08
dc.identifier.isbn978-1-4503-9237-2
dc.identifier.urihttps://hdl.handle.net/1721.1/146162
dc.publisherACM|Genetic and Evolutionary Computation Conferenceen_US
dc.relation.isversionofhttps://doi.org/10.1145/3512290.3528844en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceACM|Genetic and Evolutionary Computation Conferenceen_US
dc.titleAnalyzing Multi-Agent Reinforcement Learning and Coevolution in Cybersecurityen_US
dc.typeArticleen_US
dc.identifier.citationTurner, Matthew, Hemberg, Erik and O'Reilly, Una-May. 2022. "Analyzing Multi-Agent Reinforcement Learning and Coevolution in Cybersecurity."
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-11-03T00:17:41Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2022-11-03T00:17:42Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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