Over the last quarter century, the dominant tendency in comparative cognitive psychology
has been to emphasize the similarities between human and nonhuman minds and to …

The authors outline a cognitive and computational account of causal learning in children.
They propose that children use specialized cognitive systems that allow them to recover an …

Inducing causal relationships from observations is a classic problem in scientific inference,
statistics, and machine learning. It is also a central part of human learning, and a task that …

Speed in acquiring the knowledge and skills to perform tasks is crucial. Yet, it still ordinarily
takes many years to achieve high proficiency in countless jobs and professions, in …

Over the past decade, an active line of research within the field of human causal learning
and inference has converged on a general representational framework: causal models …

The article presents a Bayesian model of causal learning that incorporates generic priors--
systematic assumptions about abstract properties of a system of cause-effect relations. The …

This study examines preschoolers' causal assumptions about spatial contiguity and how
these assumptions interact with new evidence in the form of conditional probabilities …

Over the past 30 years we have discovered an enormous amount about what children know
and when they know it. But the real question for developmental cognitive science is not so …

Three studies investigated children's belief in causal determinism. If children are
determinists, they should infer unobserved causes whenever observed causes appear to act …

What do children's interactions on the playground have to do with foreign policy? How does
science understanding in middle school relate to environmental disasters in third world …