This chapter examines two approaches to resolving the question of how prior knowledge and current knowledge interact in category learning. The first relies on mathematical models of statistical inference. The second is an implemented connectionist computational model. To illustrate the usefulness of these latter models, the chapter develops a possible connectionist model of how prior knowledge and on-line learning integrate during early concept learning.