higher-order/polynomial units in human learning models

[Mark Gluck]

The use of "higher-order" or polynomial units also has a long
tradition in animal and human learning theory where they are
called "configural-cues." We have found that such units, combined
with the LMS algorithm, do quite well in predicting and fitting
a wide range of complex human classification and recognition
behaviors (often better than base-line backprop networks).

This work is described in:

Gluck, Bower, & Hee (1989). A configural-cue network model of animal
   and human associative learning. Proceedings of the Eleventh Annual
   Meeting of the Cognitive Science Society, Ann Arbor, MI. Lawrence
   Erlbaum Associates: Hillsdale, NJ

Reprint requests can be sent to: gluck at psych.stanford.edu