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dc.contributor.authorReaz, M.en_US
dc.contributor.authorAssim, A.en_US
dc.contributor.authorIbrahimy, M.en_US
dc.contributor.authorChoong, F.en_US
dc.contributor.authorMohd-Yasin, F.en_US
dc.contributor.editorHamid R. Arabnia ...[et al.]en_US
dc.date.accessioned2017-05-03T11:49:39Z
dc.date.available2017-05-03T11:49:39Z
dc.date.issued2008en_US
dc.date.modified2013-02-13T23:55:12Z
dc.identifier.urihttp://hdl.handle.net/10072/40614
dc.description.abstractFuture Smart-Home device usage prediction is a very important module in artificial intelligence. The technique involves analyzing the user performed actions history and apply mathematical methods to predict the most feasible next user action. Unfortunately most of the techniques tend to ignore the adaptation to the user preferred actions and the relation between the actions and the state of the environment which is not practical for Smart-Home systems. This paper present a new algorithm of user action prediction based on pattern matching and techniques of reinforcement learning. The algorithm is modeled using hardware description language VHDL. Synthetic data had been used to test the algorithm and the result shows that the algorithm performs realistically better than the current available techniquesen_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.format.extent798865 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherCSREAen_US
dc.publisher.placeLas Vegasen_US
dc.publisher.urihttp://www.world-academy-of-science.org/worldcomp08/ws/conferences/mlmta08en_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofconferencename2008 international conference on machine learning: models, technologies and applications (MLMTA'08)en_US
dc.relation.ispartofconferencetitleProceedings of the 2008 international conference on machine learning: models, technologies and applications (MLMTA'08)en_US
dc.relation.ispartofdatefrom2008-07-14en_US
dc.relation.ispartofdateto2008-07-17en_US
dc.relation.ispartoflocationLas Vegasen_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchElectrical and Electronic Engineering not elsewhere classifieden_US
dc.subject.fieldofresearchcode090699en_US
dc.titleHardware Simulation of Home Automation Using Pattern Matching and Reinforcement Learning for Disabled Peopleen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.rights.copyrightCopyright 2008 CSREA. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.en_US
gro.date.issued2008
gro.hasfulltextFull Text


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    Contains papers delivered by Griffith authors at national and international conferences.

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