Proceedings of the Annual Meeting of the Cognitive Science Society

The aim of this paper is to introduce a simple connectionist model for the acquisition of word meaning, and to demonstrate how this model can be enhanced based on empirical observations about language learning in children. The main sources are observations by Markman (1989, 1990) about constraints children place on word meaning, and Nelson (1988), as well as Benelli (1988), about the role of language in the acquisition of concept taxonomies. The model enhancements based on these observations, and those authors' conclusions, are mainly built on well-known neural mechanisms such as resonance, reset and recruitment, as first introduced in the adaptive resonance theory (ART) models by Grossberg (1976). This way the strength of connectionist models in plausibly modeling detailed aspects of natural language is underlined.