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dc.contributor.authorPage, M.P.A.
dc.date.accessioned2012-01-25T13:01:08Z
dc.date.available2012-01-25T13:01:08Z
dc.date.issued2000
dc.identifier.citationPage , M P A 2000 , ' Connectionist modelling in psychology : a localist manifesto ' , Behavioral and Brain Sciences , vol. 23 , no. 04 , pp. 443-467 . < http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=65457&fulltextType=RA&fileId=S0140525X00003356 >
dc.identifier.issn1469-1825
dc.identifier.otherBibtex: urn:7af1431561b851e6fff32e08c4b58433
dc.identifier.urihttp://hdl.handle.net/2299/7720
dc.description.abstractOver the last decade, fully distributed models have become dominant in connectionist psychological modelling, whereas the virtues of localist models have been underestimated. This target article illustrates some of the benefits of localist modelling. Localist models are characterized by the presence of localist representations rather than the absence of distributed representations. A generalized localist model is proposed that exhibits many of the properties of fully distributed models. It can be applied to a number of problems that are difficult for fully distributed models, and its applicability can be extended through comparisons with a number of classic mathematical models of behaviour. There are reasons why localist models have been underused, though these often misconstrue the localist position. In particular, many conclusions about connectionist representation, based on neuroscientific observation, can be called into question. There are still some problems inherent in the application of fully distributed systems and some inadequacies in proposed solutions to these problems. In the domain of psychological modelling, localist modelling is to be preferred.en
dc.format.extent25
dc.format.extent562650
dc.language.isoeng
dc.relation.ispartofBehavioral and Brain Sciences
dc.titleConnectionist modelling in psychology : a localist manifestoen
dc.contributor.institutionHealth & Human Sciences Research Institute
dc.contributor.institutionSchool of Life and Medical Sciences
dc.contributor.institutionDepartment of Psychology
dc.contributor.institutionPsychology
dc.contributor.institutionLearning, Memory and Thinking
dc.description.statusPeer reviewed
dc.identifier.urlhttp://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=65457&fulltextType=RA&fileId=S0140525X00003356
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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