Running head: THEORY FORMATION A probabilistic model of theory formation

Concept learning is challenging in part because the meanings of many concepts depend on their relationships to other concepts. Learning these concepts in isolation can be difficult, but we present a model that discovers entire systems of related concepts. These systems can be viewed as simple theories that specify the concepts that exist in a domain, and the laws or principles that relate these concepts. We apply our model to several real-world problems, including learning the structure of kinship systems and learning ontologies. We also compare its predictions to data collected in two behavioral experiments. Experiment 1 shows that our model helps to explain how simple theories are acquired and used for inductive inference. Experiment 2 suggests that our model provides a better account of theory discovery than a more traditional alternative that focuses on features rather than relations. 2 A probabilistic model of theory formation Parent: A person who has begotten or borne a child. Child: The offspring, male or female, of human parents. The Oxford English Dictionary, 2nd edition, 1989. Samuel Johnson acknowledges that his dictionary of 1755 is far from perfect, but suggests that “many seeming faults are to be imputed rather to the nature of the undertaking, than the negligence of the performer. ” He argues, for instance, that “some explanations are unavoidably reciprocal or circular, as hind, the female of the stag; stag, the male of the hind. ” Analogies between dictionary definitions and mental representations can only extend so far, but Johnson appears to have uncovered a general truth about the structure of human knowledge. Scholars from many disciplines have argued that concepts are organized into systems of relations, and tha