Interleaving examples of to-be-learned categories, rather than blocking examples by category, frequently enhances category induction. The presently dominant theory is that interleaving promotes discriminative-contrast, and suggests that category similarity structure modulates this interleaving benefit: that blocking should benefit learning when…

This paper describes further research on a learning procedure for layered networks of deterministic, neuron-like units, described by Rumelhart et al. The units, the way they are connected, the learning procedure, and the extension to iterative networks are presented. In one experiment, a network learns a set of filters, enabling it to discriminate…