Behavioral and Brain Sciences

Short Communication

Extending Bayesian concept learning to deal with representational complexity and adaptation

Michael D. Lee a1
a1 Department of Psychology, University of Adelaide, SA 5008 Australia


While Tenenbaum and Griffiths impressively consolidate and extend Shepard's research in the areas of stimulus representation and generalization, there is a need for complexity measures to be developed to control the flexibility of their “hypothesis space” approach to representation. It may also be possible to extend their concept learning model to consider the fundamental issue of representational adaptation. [Tenenbaum & Griffiths]