Literature DB >> 16047456

The rules versus similarity distinction.

Emmanuel M Pothos1.   

Abstract

The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be described on the basis of separate models. In the present article, I assume that the rules versus similarity distinction can be understood in the same way in learning, reasoning, categorization, and language, and that a unified model for rules and similarity is appropriate. A rules process is considered to be a similarity one where only a single or a small subset of an object's properties are involved. Hence, rules and overall similarity operations are extremes in a single continuum of similarity operations. It is argued that this viewpoint allows adequate coverage of theory and empirical findings in learning, reasoning, categorization, and language, and also a reassessment of the objectives in research on rules versus similarity.

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Year:  2005        PMID: 16047456     DOI: 10.1017/s0140525x05000014

Source DB:  PubMed          Journal:  Behav Brain Sci        ISSN: 0140-525X            Impact factor:   12.579


  18 in total

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Journal:  Psychol Res       Date:  2015-10-20

3.  Dual-task interference in perceptual category learning.

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Journal:  Mem Cognit       Date:  2006-03

4.  Tracking mouse movement in feature inference: category labels are different from feature labels.

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Journal:  Mem Cognit       Date:  2007-07

5.  Incidental learning of abstract rules for non-dominant word orders.

Authors:  Andrea P Francis; Gwen L Schmidt; Thomas H Carr; Benjamin A Clegg
Journal:  Psychol Res       Date:  2008-03-05

6.  Connectionist models of artificial grammar learning: what type of knowledge is acquired?

Authors:  Annette Kinder; Anja Lotz
Journal:  Psychol Res       Date:  2008-11-08

7.  Categorization of novel tools by patients with Alzheimer's disease: category-specific content and process.

Authors:  Phyllis Koenig; Edward E Smith; Murray Grossman
Journal:  Neuropsychologia       Date:  2009-08-05       Impact factor: 3.139

8.  Use of evidence in a categorization task: analytic and holistic processing modes.

Authors:  Alberto Greco; Stefania Moretti
Journal:  Cogn Process       Date:  2017-08-14

9.  Visual Learning of Statistical Relations Among Non-adjacent Features: Evidence for Structural Encoding.

Authors:  Elan Barenholtz; Michael J Tarr
Journal:  Vis cogn       Date:  2011-04-01

10.  Does practice in category learning increase rule use or exemplar use-or both?

Authors:  Jean-Pierre Thibaut; Sabine Gelaes; Gregory L Murphy
Journal:  Mem Cognit       Date:  2018-05
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