ALCOVE: A Connectionist Model of Human Category Learning

Part of Advances in Neural Information Processing Systems 3 (NIPS 1990)

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John Kruschke


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.