Proceedings of the Annual Meeting of the Cognitive Science Society

An unusual asymmetry has been observed in natural category formation in infants (Quinn, Eimas, and Rosenkrantz, 1993). Infants who are initially exposed to a series of pictures of cats and then are shown a dog and a novel cat, show significantly more interest in the dog than in the cat, However, when the order of presentation is reversed — dogs are seen first, then a cat and a novel dog — the cat attracts no more attention than the dog. We show that a simple connectionist network can model this unexpected learning asymmetry and propose that this asymmetry arises naturally from the asymmetric overlaps of the feature distributions of the two categories. The values of the cat features are subsumed by those of dog features, but not vice-versa. The autoencoder used for the experiments presented in this paper also reproduces exclusivity effects in the two categories as well the reported effect of catastrophic interference of dogs on previously learned cats, but not vice-versa. The results of the modeling suggest connectionist methods are ideal for exploring early infant knowledge acquisition.