All students of cognitive development agree that the central questions in development are 1) specifying the initial state of a human infant, 2) specifying the final state of development for a human adult, and 3) specifying how to get from the initial state to the final state. Then academic disputes ensue. Cognitive developmental psychologists are roughly divided into two camps: those who are more or less nativists and those who are more or less empiricists. Some psychologists do not like these terms, and some alternatives are “those who believe in innate knowledge ” and “those who believe in learning, ” or “those who believed in initial conceptual knowledge ” and “those who believe in initial perceptual capabilities. ” This division is also correlated with whether a researcher believes in domain specificity or not: nativists tend to argue for domain-specific knowledge (even at the beginning of development) and domain-specific learning mechanisms; empiricists tend to argue for domain-general learning mechanisms that may result in domain-specific knowledge some years into development (for some representative explications of these views, see Carey &

We outline a new computational account of learning in children using the causal Bayes net formalism. We also present evidence that children as young as two years old use something like causal Bayes net learning mechanisms to infer the causal structure of the world around them. This kind of learning may play an important role in the development of intuitive theories. Finally we contrast causal Bayes net and neural net learning mechanisms.