title: Optimal predictions in everyday cognition.
abstract: Human perception and memory are often explained as optimal statistical inferences that are informed by accurate prior probabilities. In contrast, cognitive judgments are usually viewed as following error-prone heuristics that are insensitive to priors. We examined the optimality of human cognition in a more realistic context than typical laboratory studies, asking people to make predictions about the duration or extent of everyday phenomena such as human life spans and the box-office take of movies. Our results suggest that everyday cognitive judgments follow the same optimal statistical principles as perception and memory, and reveal a close correspondence between people's implicit probabilistic models and the statistics of the world.
authors.affiliation: Department of Cognitive and Linguistic Sciences, Brown University, RI 02912, USA. tom_griffiths@brown.edu
authors.forename: Thomas L
authors.initials: TL
authors.lastname: Griffiths
authors.forename: Joshua B
authors.initials: JB
authors.lastname: Tenenbaum
mesh_terms: D003071:Cognition; D005544:Forecasting; D006801:Humans; D008568:Memory; D015233:Models, Statistical; D010465:Perception; D011584:Psychology / Q000706:statistics & numerical data