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M K Johansen

Publications and source records attributed to M K Johansen.

2 recordsLinked to original sources

Exemplar-based accounts of "multiple-system" phenomena in perceptual categorization.

We demonstrate that a wide variety of recently reported "rule-described" and "prototype-described" phenomena in perceptual classification, which have led to the development of a number of multiple-system models, can be given an alternative interpretation in terms of a single-system exemplar-similarity model. The phenomena include various rule- and prototype-described patterns of generalization, dissociations between categorization and similarity judgments, and dissociations between categorization and old-new recognition. The alternative exemplar-based interpretation relies on the idea that similarity is not an invariant relation but a context-dependent one. Similarity relations among exemplars change systematically because of selective attention to dimensions and because of changes in the level of sensitivity relating judged similarity to distance in psychological space. Adaptive learning principles may help explain the systematic influence of the selective attention process and of modulation in sensitivity settings on judged similarity.

Adult↗

A model of probabilistic category learning.

A new connectionist model (named RASHNL) accounts for many "irrational" phenomena found in nonmetric multiple-cue probability learning, wherein people learn to utilize a number of discrete-valued cues that are partially valid indicators of categorical outcomes. Phenomena accounted for include cue competition, effects of cue salience, utilization of configural information, decreased learning when information is introduced after a delay, and effects of base rates. Experiments 1 and 2 replicate previous experiments on cue competition and cue salience, and fits of the model provide parameter values for making qualitatively correct predictions for many other situations. The model also makes 2 new predictions, confirmed in Experiments 3 and 4. The model formalizes 3 explanatory principles: rapidly shifting attention with learned shifts, decreasing learning rates, and graded similarity in exemplar representation.

Cues↗