Literature DB >> 24213871

Learning to classify integral-dimension stimuli.

R M Nosofsky1, T J Palmeri.   

Abstract

The authors tested 288 participants in the classic category-learning tasks introduced by Shepard, Hovland, and Jenkins (1961). However, separable-dimension stimuli were used in previous tests, whereas integral-dimension stimuli were used in the present study. In contrast to previous results, which showed a superiority for Problem Type II over Problem Types III, IV, and V, the reverse pattern was observed in the present research. This result confirms a fundamental prediction made by modern exemplar-based models of classification learning. The results are interpreted in terms of the extent to which selective-attention learning mechanisms operate when separable-dimension versus integral-dimension stimuli are used.

Entities:  

Year:  1996        PMID: 24213871     DOI: 10.3758/BF03212422

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  4 in total

1.  Stimulus generalization in the learning of classifications.

Authors:  R N SHEPARD; J J CHANG
Journal:  J Exp Psychol       Date:  1963-01

2.  ALCOVE: an exemplar-based connectionist model of category learning.

Authors:  J K Kruschke
Journal:  Psychol Rev       Date:  1992-01       Impact factor: 8.934

3.  Comparing models of rule-based classification learning: a replication and extension of Shepard, Hovland, and Jenkins (1961).

Authors:  R M Nosofsky; M A Gluck; T J Palmeri; S C McKinley; P Glauthier
Journal:  Mem Cognit       Date:  1994-05

4.  Choice, similarity, and the context theory of classification.

Authors:  R M Nosofsky
Journal:  J Exp Psychol Learn Mem Cogn       Date:  1984-01       Impact factor: 3.051

  4 in total
  18 in total

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

Authors:  R M Nosofsky; M K Johansen
Journal:  Psychon Bull Rev       Date:  2000-09

2.  Single-system models and interference in category learning: commentary on Waldron and Ashby (2001).

Authors:  Robert M Nosofsky; John K Kruschke
Journal:  Psychon Bull Rev       Date:  2002-03

3.  Comparing supervised and unsupervised category learning.

Authors:  Bradley C Love
Journal:  Psychon Bull Rev       Date:  2002-12

4.  Learning categories at different hierarchical levels: a comparison of category learning models.

Authors:  T J Palmeri
Journal:  Psychon Bull Rev       Date:  1999-09

5.  The divergent autoencoder (DIVA) model of category learning.

Authors:  Kenneth J Kutrz
Journal:  Psychon Bull Rev       Date:  2007-08

6.  Information-processing architectures in multidimensional classification: a validation test of the systems factorial technology.

Authors:  Mario Fific; Robert M Nosofsky; James T Townsend
Journal:  J Exp Psychol Hum Percept Perform       Date:  2008-04       Impact factor: 3.332

7.  Reinforcement learning in multidimensional environments relies on attention mechanisms.

Authors:  Yael Niv; Reka Daniel; Andra Geana; Samuel J Gershman; Yuan Chang Leong; Angela Radulescu; Robert C Wilson
Journal:  J Neurosci       Date:  2015-05-27       Impact factor: 6.167

8.  The Interplay between Feature-Saliency and Feedback Information in Visual Category Learning Tasks.

Authors:  Rubi Hammer; Vladimir Sloutsky; Kalanit Grill-Spector
Journal:  Cogsci       Date:  2012

9.  Logical-rules and the classification of integral dimensions: individual differences in the processing of arbitrary dimensions.

Authors:  Anthea G Blunden; Tony Wang; David W Griffiths; Daniel R Little
Journal:  Front Psychol       Date:  2015-01-09

10.  On the learning difficulty of visual and auditory modal concepts: Evidence for a single processing system.

Authors:  Ronaldo Vigo; Karina-Mikayla C Doan; Charles A Doan; Shannon Pinegar
Journal:  Cogn Process       Date:  2017-10-26
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