title: Alignment-based nonmonotonicities in similarity.
abstract: According to the assumption of monotonicity in similarity judgments, adding a shared feature in common to 2 items should never decrease their similarity. Violations of monotonicity are not predicted by feature- or dimension-based models but can be accommodated by alignment-based models in which the parts of one compared display are placed in correspondence with the parts of the other display. In 2 experiments, evidence for nonmonotonicities is obtained that is generally consistent with the alignment-based model SIAM (similarity as interactive activation and mapping; R.L. Goldstone, 1994). The calculation of similarity in this model involves an interactive activation process whereby correspondences between the parts of compared displays mutually and concurrently influence each other. As SIAM predicts, the occurrence of nonmonotonicities depends on perceptual similarity of features and the duration of presented comparison.
authors.affiliation: Psychology Department, Indiana University, Bloomington 47405, USA. rgoldsto@indiana.edu
authors.forename: R L
authors.initials: RL
authors.lastname: Goldstone
mesh_terms: D000328:Adult; D001288:Attention; D003118:Color Perception; D004193:Discrimination Learning; D005260:Female; D006801:Humans; D008297:Male; D009949:Orientation; D010364:Pattern Recognition, Visual; D011601:Psychophysics; D012691:Serial Learning