Proceedings of the Annual Meeting of the Cognitive Science Society

Recent research has shown that the prior knowledge of the learner influences both how quickly a concept is learned and the types of generalizations that a learner produces. W e investigate two learning frameworks that have been proposed to account for these findings. Here, w e contrast/eamre selection models of learnmg wu\a hypothesis selection models. W e report on an experiment that suggests that human learners use prior knowledge both to indicate what features may be relevant and to influence how the features are combined to form hypotheses. W e present an extension to the PostHoc system, a hypothesis selection model of concept learning, that is able to account for differences in learning rates observed in the experiment.