THE DEVELOPMENT OF FEATURES IN OBJECT CONCEPTS

According to one productive and influential approach to cognition, cat egorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower leve l perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of feat ures as being fixed by low-level processes, we present a theory in whi ch people create features to subserve the representation and categoriz ation of objects. Two types of category learning should be distinguish ed. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with th e features available. Whether fixed or flexible, learning depends on t he featural contrasts and similarities between the new category to be represented and the individual's existing concepts. Fixed feature appr oaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for c ategorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features a re small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categoriz ations will not be captured by these primitives. We present evidence o f flexible perceptual changes arising from category learning and theor etical arguments for the importance of this flexibility. We describe c onditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual developm ent, chunking, constructive induction, and formal models of dimensiona lity reduction.