# Mechanisms of theory formation in young children **Abstract:** representations of the causal structure of the world. Even the youngest preschoolers can use these intuitive theories to make causal predictions, provide causal explanations, and reason about causation counterfactually [4–7]. Moreover, both studies of natural variation in relevant experiences, and explicit training studies, demonstrate that children’s intuitive theories change in response to evidence [8–11]. But the real question for developmental cognitive science is not so much what children know and when they know it, but how children’s theories develop and change and why children’s theories converge towards accurate descriptions of the world. It is all very well to suggest that children’s learning mechanisms are analogous to scientific theory-formation. However, what we would really like is a more precise specification of the mechanisms that underlie learning in both scientists and children. One such candidate learning mechanism has recently attracted considerable interest within the fields of computer science, philosophy and psychology. The causal Bayes net account of causal knowledge and learning provides computational learning procedures that allow abstract, coherent, structured representations to be derived from patterns of evidence, given certain Corresponding author: Alison Gopnik ([email protected]). Available online 8 July 2004 assumptions [12–15]. One advantage of this formal learning account is that it specifies, with some precision, the kinds of abil **Authors:** [[Alison Gopnik and Laura Schulz]]