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• W1567697177 abstract "This chapter reviews the relative merits of a variety of category learning models. These include rule-based models, prototype-based models, exemplar-based models, hybrid models, and multiple systems models. All of these models have played a critical role in driving advances in theory and in the design of key experiments. The development of new models is informed by the failings of preceding models." @default.
• W1567697177 created "2016-06-24" @default.
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• W1567697177 date "2010-01-14" @default.
• W1567697177 modified "2023-10-13" @default.
• W1567697177 title "Mechanistic models of associative and rule-based category learning" @default.
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• W1567697177 doi "https://doi.org/10.1093/acprof:oso/9780199549221.003.04" @default.
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