ALCOVE: A Connectionist Model of Human Category Learning
Abstract
ALCOVE is a connectionist model of human category learning that fits a broad spectrum of human learning data. Its architecture is based on well(cid:173) established psychological theory, and is related to networks using radial basis functions. From the perspective of cognitive psychology, ALCOVE can be construed as a combination of exemplar-based representation and error(cid:173) driven learning. From the perspective of connectionism, it can be seen as incorporating constraints into back-propagation networks appropriate for modelling human learning.
Cite
Text
Kruschke. "ALCOVE: A Connectionist Model of Human Category Learning." Neural Information Processing Systems, 1990.Markdown
[Kruschke. "ALCOVE: A Connectionist Model of Human Category Learning." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/kruschke1990neurips-alcove/)BibTeX
@inproceedings{kruschke1990neurips-alcove,
title = {{ALCOVE: A Connectionist Model of Human Category Learning}},
author = {Kruschke, John K.},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {649-655},
url = {https://mlanthology.org/neurips/1990/kruschke1990neurips-alcove/}
}