SIMILARITY IN A DISTRIBUTED-MEMORY MODEL

Similarity is an important variable in the study of cognitive processes. This paper describes an approach to similarity using correlated random vectors where the similarity between two items is given by rho, the theoretical correlation coefficient of the bivariate normal distribution. It is shown how to implement this approach in TODAM, a theory of distributed associative memory, and closed-form expressions are derived. Applications to the list-strength and the list-length effect are presented, and it is shown that the model gives a good quantitative account of the list-length effect at the level of the individual subject. (C) 1995 Academic Press. Inc.