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.

Its architecture is based on wellestablished psychological theory, and is related to networks using radial basis functions.

Its architecture is based on wellestablished psychological theory, and is related to networks using radial basis functions.

Its architecture is based on wellestablished psychologicaltheory, and is related to networks using radial basis functions.