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dc.contributor.authorLane, P.C.R.
dc.contributor.authorGobet, F.
dc.contributor.authorSmith, R.L.
dc.date.accessioned2009-05-13T14:36:23Z
dc.date.available2009-05-13T14:36:23Z
dc.date.issued2009
dc.identifier.citationLane , P C R , Gobet , F & Smith , R L 2009 , ' Attention Mechanisms in the CHREST Cognitive Architecture ' , Lecture Notes in Computer Science (LNCS) , vol. 5395 , pp. 183-196 . https://doi.org/10.1007/978-3-642-00582-4_14
dc.identifier.issn0302-9743
dc.identifier.otherdspace: 2299/3368
dc.identifier.urihttp://hdl.handle.net/2299/3368
dc.descriptionIn: Proceedings of the Fifth International Workshop on Attention in Cognitive Systems, edited by Paletta, L.; Tsotsos, J.K.(Springer-Verlag) “The original publication is available at www.springerlink.com”. Copyright Springer. DOI: 10.1007/978-3-642-00582-4_14
dc.description.abstractIn this paper, we describe the attention mechanisms in CHREST, a computational architecture of human visual expertise. CHREST organises information acquired by direct experience from the world in the form of chunks. These chunks are searched for, and verified, by a unique set of heuristics, comprising the attention mechanism. We explain how the attention mechanism combines bottom-up and top-down heuristics from internal and external sources of information. We describe some experimental evidence demonstrating the correspondence of CHREST’s perceptual mechanisms with those of human subjects. Finally, we discuss how visual attention can play an important role in actions carried out by human experts in domains such as chess.en
dc.format.extent145794
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science (LNCS)
dc.titleAttention Mechanisms in the CHREST Cognitive Architectureen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.1007/978-3-642-00582-4_14
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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