Proceedings of the Annual Meeting of the Cognitive Science Society

This paper describes an implemented computational model of lexical development for the case of action verbs. A simulated agent is trained by an informant labeling the agent's actions (here hand motions), and the system learns to both label and carry out similar actions. The verb learning model is placed in the broader context of the NTL project on embodied natural language and its acquisition. Based on experimental results and projections to the full range of early lexemes, a significantly enriched model is proposed and its properties discussed.