Concept Learning Rates and Transfer Performance of Several Multivariate Neural Network Models

The purpose of this chapter is to present results for several related learning models, which may be useful both in machine learning and in the analysis of human learning. One motivation has been our desire to develop efficient and powerful methods of concept learning to use in our work on machine learning of natural language (Suppes, Böttner, & Liang, 1995; Suppes, Liang, & Böttner, 1992). In this earlier work, concepts were assumed known and the learning concentrated on language. It is obviously important to combine both concept and language learning for many kinds of situations. In unpublished research we have already used the learning models proposed here in the early stages of robotic concept and language learning.