http://cogprints.org/5917/
How training and testing histories affect generalization: a test of simple neural networks
We show that a simple network model of associative learning can
reproduce three findings that arise from particular training and
testing procedures in generalization experiments: the effect of 1)
``errorless learning'' and 2) extinction testing on peak shift, and
3) the central tendency effect. These findings provide a true test
of the network model, which was developed to account for other
penhomena, and highlight the potential of neural networks to study
phenomena that depend on sequences of experiences with many stimuli.
Our results suggest that at least some such phenomena, e.g.,
stimulus range effects, may derive from basic mechanisms of
associative memory rather than from more complex memory processes.
Ghirlanda, Stefano
Enquist, Magnus
Animal Cognition
Computational Neuroscience
Neural Modelling
Ethology
Animal Behavior
Comparative Psychology
Stefano
Ghirlanda
Magnus
Enquist