models of attention

[kruschke@ucs.indiana.edu]

All the responses (that I've seen) to Peter Marvit's query about attention have
concerned *visual/spatial* attention, and mostly the feature-integration
problem at that. 

But ``attention'' is used in other ways in the psych literature.  In
particular, it is often used to describe which information in a stimulus is
deemed to be relevant by the subject when making ``high-level'' decisions, such
as which category the stimulus belongs to.  Consider, for example, a medical
diagnosis situation, in which several different symptoms are present, but only
some are ``attended to'' by the physician, because the physician has learned
that only some types of symptoms are relevant. 

This type of attention has been described in the connectionist literature as 
well.  Two references immediately come to mind (no doubt there are others;
readers, please inform us):  Mozer and Smolensky, ``Skeletonization...''
in NIPS'88; and Gluck & Chow, ``Dynamic stimulus specific learning rates...'' 
in NIPS'89.

I am presently working on a model, called ALCOVE, that learns to distribute
attention across input dimensions during training.  It captures many effects
observed in human category learning, such as the relative difficulty of
different types of category structures, some types of base-rate neglect,
learning speeds of rules and exceptions (including U-shaped learning of
high-frequency exceptions), etc. It is written up in my PhD thesis, to be
announced in a few weeks. 


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  John K. Kruschke                    kruschke at ucs.indiana.edu
  Dept. of Psychology                 kruschke at iubacs.bitnet
  Indiana University                  (812) 855-3192
  Bloomington, IN 47405-4201 USA
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