Early research in the field of intuitive physics provided extensive evidence that humans
succumb to common misconceptions and biases when predicting, judging, and explaining …

The ability to act on the world with the goal of gaining information is core to human
adaptability and intelligence. Perhaps the most successful and influential account of such …

We present a differentiable physics engine that can be integrated as a module in deep
neural networks for end-to-end learning. As a result, structured physics knowledge can be …

The human ability to reason about the causes behind other people'behavior is critical for
navigating the social world. Recent empirical research with both children and adults …

People's decisions and judgments are disproportionately swayed by improbable but
extreme eventualities, such as terrorism, that come to mind easily. This article explores …

This chapter first explains what intuitive theories are, how they can be modeled as
probabilistic, generative programs, and how intuitive theories support various cognitive …

Higher-level cognition depends on the ability to learn models of the world. We can
characterize this at the computational level as a structure-learning problem with the goal of …

Human probability judgments are systematically biased, in apparent tension with Bayesian
models of cognition. But perhaps the brain does not represent probabilities explicitly, but …

Why are human inferences sometimes remarkably close to the Bayesian ideal and other
times systematically biased? In particular, why do humans make near-rational inferences in …

After observing a collision between two boxes, you can immediately tell which is empty and
which is full of books based on how the boxes moved. People form rich perceptions about …