Intent recognition of autonomous agents

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dc.check.chapterOfThesisNot applicableen
dc.contributor.advisorBrown, Kenneth
dc.contributor.advisorWilson, Nic
dc.contributor.authorNaeem, Ali A.en
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2024-05-29T11:19:08Z
dc.date.available2024-05-29T11:19:08Z
dc.date.issued2024
dc.date.submitted2024
dc.description.abstractThis research develops a hierarchical framework that utilizes machine learning models and manifold learning techniques to infer the intent of autonomous agents from their observed actions. Through three distinct implementation examples—activities of daily living in a smart home, access control in an office building, and predicting vehicle destinations—this thesis demonstrates the applicability and effectiveness of the proposed framework in real-world scenarios. The framework presented narrows the design space for a machine learning practitioner who wishes to carry out intent recognition on a new data set by providing a structured approach to tackle the problem.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationNaeem, A. A. 2024. Intent recognition of autonomous agents. PhD Thesis, University College Cork.
dc.identifier.endpage177
dc.identifier.urihttps://hdl.handle.net/10468/15945
dc.language.isoenen
dc.publisherUniversity College Corken
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres Programme::Phase 2/12/RC/2289-P2s/IE/INSIGHT Phase 2/en
dc.rights© 2024, Ali Azzam Naeem.
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectIntent recognition
dc.subjectHierarchical framework
dc.subjectAutonomous agents
dc.subjectManifold learning
dc.subjectSmart homes
dc.subjectAccess control systems
dc.subjectVehicle trajectory prediction
dc.subjectMachine learning
dc.subjectArtificial intelligence
dc.titleIntent recognition of autonomous agents
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD - Doctor of Philosophyen
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