TR Announcement: Rules and exemplars in category learning

[John Kruschke]

          Rules and Exemplars in Category Learning

          Michael A. Erickson and John K. Kruschke
              Indiana University, Bloomington

Psychological theories of categorization have generally focused on
either rule- or exemplar-based explanations of categorization. We
present two experiments that show evidence of both rule induction and
exemplar encoding, and we present a connectionist model (ATRIUM) that
specifies a mechanism for combining rule- and exemplar-based
representation. In both experiments participants learned to classify
items, most of which followed a simple rule although there were a few,
frequently occurring exceptions. Experiment 1 examined how people
extrapolate beyond the range of trained instances.  Experiment 2
examined the effects of instance frequency on generalization to novel
cases. We found that categorization behavior was well described by the
model, in which exemplar representation is used for both rule and
exception processing. A key element in correctly modeling
categorization in tasks such as these was capturing the interaction
between the rule- and exemplar-based representational structures using
shifts of attention between rules and exemplars.

This report is also available for electronic retrieval (uncompressed
PostScript, 589 Kbytes) from
  http://www.indiana.edu/~kruschke/ek96_abstract.html
A very limited number of paper copies are also available; request
Cognitive Science Technical Report #183, by Erickson & Kruschke, from
iucogsci at indiana.edu

-- 
John K. Kruschke                          office: (812) 855-3192
Dept. of Psychology                          fax: (812) 855-4691
Indiana University             http://www.indiana.edu/~kruschke/
Bloomington, IN 47405-1301                  kruschke at indiana.edu