In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to…

We study people's abilities to transfer object category knowledge across visual and haptic domains. If a person learns to categorize objects based on inputs from one sensory modality, can the person categorize these same objects when the objects are perceived through another modality? Can the person categorize novel objects from the same…

This paper investigates the classification of shapes into broad natural categories such as "animal" or "leaf". We asked whether such coarse classifications can be achieved by a simple statistical classification of the shape skeleton. We surveyed databases of natural shapes, extracting shape skeletons and tabulating their…

Probabilistic models of expected information gain require integrating prior knowledge about causal hypotheses with knowledge about possible actions that might generate data relevant to those hypotheses. Here we looked at whether preschoolers (mean: 54 months) recognize "action possibilities" (affordances) in the environment that allow them to…