### Abstract

An intuitive theory is a system of abstract concepts and laws relating those concepts that together provide a framework for explaining some domain of phenomena. Constructing an intuitive theory based on observing the world, as in building a scientific theory from data, confronts learners with a “chicken-and-egg” problem: the laws can only be expressed in terms of the theory’s core concepts, but these concepts are only meaningful in terms of the role they play in the theory’s laws; how is a learner to discover appropriate concepts and laws simultaneously, knowing neither to begin with? Even knowing the number of categories in a theory does not resolve this problem: without knowing how individuals should be sorted (which categories each belongs to), a the causal relationships between categories cannot be resolved. We explore how children can solve this chicken-and-egg problem in the domain of magnetism, drawing on perspectives from history of science, computational modeling, and behavioral experiments. We present preschoolers with a simplified magnet learning task and show how our empirical results can be explained as rational inferences within a Bayesian computational framework.

Publication

*2012 IEEE International Conference on Development and Learning and Epigenetic Robotics*

###### Primary Investigator

My research focuses on the structure and origin of knowledge, guided by perspectives and methods from cognitive science, cognitive development, and computational modeling. By combining these, I hope to better understand the form and development of the basic commonsense reasoning that guides our interaction with the world and the people in it.