Patterson, Snoddy, & Kurtz (2019) Family Resemblance in unsupervised categorization: A dissociation between production and evaluation.

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Abstract

A plurality of the categories we hold exhibit family resemblance (FR; i.e., many characteristic but few defining features), suggesting FR may occupy a central role in human category formation. However, research in unsupervised learning has shown that when people are asked to sort an array of novel items into categories, they ubiquitously use a unidimensional (UNI) rule – despite the availability of a FR solution. This work suggests that, perhaps, FR similarity is not a core tendency in category formation. Here, we question whether the UNI bias is a result of the sorting paradigm. Specifically, we speculate the paradigm conflates two components vital for category formation: production and evaluation. Across three experiments we show that when evaluation is separated from generation – by using a novel forced-choice task that pits different category organizational schemes against one another – people exhibit a FR over UNI preference. The implications of these results are discussed.

Publication
In Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 2333-2338)
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John D. Patterson
Postdoctoral Scholar

My research interests include how we learn and represent categories, how we can optimize learning in applied settings, and how we can capture learning through computational models.