Abstract
Exemplar-based learning requires (i) a segmentation procedure for identifying the units of past experiences that a present experience can be compared to, and (ii) a similarity function for comparing these past experiences to the present experience. This article argues that for a learner to learn a language these two mechanisms will require abstractions such as linguistic features. Moreover, because the segmentation procedure will vary depending on the language, a radical exemplar theory is likely to require linguistic abstractions for learning.
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