Action and hierarchical levels of categories: A connectionist perspective

Recent views of categorization suggest that categories are action-based rather than arbitrary symbols. Three connectionist simulations explore the hierarchical organization of categories in the framework of an action-based theory of categorization. In the simulations an organism with a visual system and a two-segment arm has to reach different points in space depending on the object seen and on context. The context indicates whether to put the object in a superordinate or in a basic category. The results show that (a) superordinate categories are easier to learn than basic ones; (b) the more similar the actions to perform with basic and superordinate categories, the easier to learn the task; (c) violation of category boundaries leads to less good performance.