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

Psychol Rev. 2001 Oct;108(4):735-58. doi: 10.1037/0033-295x.108.4.735.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Concept Formation
  • Depth Perception*
  • Discrimination Learning
  • Female
  • Humans
  • Male
  • Mental Recall*
  • Pattern Recognition, Visual*
  • Problem Solving*
  • Psychophysics
  • Reaction Time