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Feature-Based Induction

dc.contributor.authorSloman S. A. ,en_US
dc.date.accessioned2006-04-10T15:48:56Z
dc.date.available2006-04-10T15:48:56Z
dc.date.issued1993-04en_US
dc.identifier.citationSloman S. A., (1993/04)."Feature-Based Induction." Cognitive Psychology 25(2): 231-280. <http://hdl.handle.net/2027.42/30872>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6WCR-45R7B72-D/2/2ecffe04e318ffc9a7bdf772831ac83ben_US
dc.identifier.urihttps://hdl.handle.net/2027.42/30872
dc.description.abstractA connectionist model of argument strength that applies to categorical arguments involving natural categories and predicates about which subjects have few prior beliefs is proposed. An example is robins have sesamoid bones, therefore falcons have sesamoid bones. The model is based on the hypothesis that argument strength is related to the proportion of the conclusion category's features that are shared by the premise categories. The model assumes a two-stage process. First, premises are encoded by connecting the features of premise categories to the predicate. Second, conclusions are tested by examining the degree of activation of the predicate upon presentation of the features of the conclusion category. The model accounts for 13 qualitative phenomena and shows close quantitative fits to several sets of argument strength ratings.en_US
dc.format.extent2452981 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleFeature-Based Inductionen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelPsychologyen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Michigan, Ann Arbor, MI, USA.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/30872/1/0000536.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1006/cogp.1993.1006en_US
dc.identifier.sourceCognitive Psychologyen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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