Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the…

Three experiments examined the effects of interactive visualizations and spatial abilities on a task requiring participants to infer and draw cross sections of a three-dimensional (3D) object. The experiments manipulated whether participants could interactively control a virtual 3D visualization of the object while performing the task, and…

We consider human performance on an optimal stopping problem where people are presented with a list of numbers independently chosen from a uniform distribution. People are told how many numbers are in the list, and how they were chosen. People are then shown the numbers one at a time, and are instructed to choose the maximum, subject to the…