Goldstone, R. L., Steyvers, M., Spencer-Smith, J., & Kersten, A. (2000). Interactions between perceptual and conceptual learning. in E. Diettrich & A. B. Markman (eds.) Cognitive Dynamics: Conceptual Change in Humans and Machines. Mahwah, New Jersey: Lawrence Erlbaum Associates. (pp. 191-228).
Confusions arise when ‘stable’ is equated with ‘foundational.’ Spurred on by the image of a house`s foundation, it is tempting to think that something provides effective support to the extent that it is rigid and stable. We will argue that when considering the role of perception in grounding our concepts, exactly the opposite is true. Our perceptual system supports our ability to acquire new concepts by being flexibly tuned to these concepts. Whereas the concepts that we learn are certainly influenced by our perceptual representations, we will argue that these perceptual representations are also influenced by the learned concepts. In keeping with one of the central themes of this book, behavioral adaptability is completely consistent with representationalism. In fact, the most straightforward account of our experimental results is that concept learning can produce changes in perceptual representations, the ‘vocabulary’ of perceptual features, that are used by subsequent tasks.
This chapter reviews theoretical and empirical evidence that perceptual vocabularies used to describe visual objects are flexibly adapted to the demands of their user. We will extend arguments made elsewhere for adaptive perceptual representations (Goldstone, Schyns, & Medin, in press; Schyns, Goldstone, & Thibaut, in press), and discuss research from our laboratory illustrating specific interactions between perceptual and conceptual learning. We will describe computer simulations that provide accounts of these interactions using neural network models. These models have detectors that become increasingly tuned to the set of perceptual features that support concept learning. The bulk of the chapter will be organized around mechanisms of human perceptual learning, and computer simulations of these mechanisms.