Bayesian Approaches to Color Category Learning

Abstract

Bayesian approaches to color category learning formalize learning as a problem of Bayesian inference, requiring the learner to form generalizations that go beyond observed examples of members of a category. This formal framework can be used to make predictions about both individual judgments and how populations form color categories.