COVIS (COmpetition between Verbal and Implicit Systems; Ashby, Alfonso-Reese, & Waldron, 1998) is a prominent model of categorization which hypothesizes that humans have two independent categorization systems - one declarative, one associative - that can be recruited to solve category learning tasks. To date, most COVIS-related research has focused on just two experimental tasks: linear rule-based (RB) tasks, which purportedly encourage declarative rule use, and linear information-integration (II) tasks, which purportedly require associative learning mechanisms. We introduce and investigate a novel alternative: the concentric-rings task, a nonlinear category structure that both humans and pigeons can successfully learn and transfer to untrained exemplars. Yet, despite their broad behavioral similarities, humans and pigeons achieve their successful learning through decidedly different means. As predicted by COVIS, pigeons appear to rely solely on associative learning mechanisms, whereas humans appear to initially test but subsequently reject unidimensional rules. We discuss how variants of our concentric-rings task might yield further insights into which category-learning mechanisms are shared across species, as well as how categorization strategies might change throughout training.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8639790PMC
http://dx.doi.org/10.1016/j.cognition.2021.104920DOI Listing

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