Why do we SLIP to the basic level? Computational constraints and their implementation.

Abstract

The authors introduce a new measure of basic-level performance (strategy length and internal practicability; SLIP). SLIP implements 2 computational constraints on the organization of categories in a taxonomy: the minimum number of feature tests required to place the input in a category (strategy length) and the ease with which these tests are performed (internal practicability). The predictive power of SLIP is compared with that of 4 other basic-level measures: context model, category feature possession, category utility, and compression measure, drawing data from other empirical work, and 3 new experiments testing the validity of the computational constraints of SLIP using computer-synthesized 3-dimensional artificial objects.

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