Marr's levels of analysis—computational, algorithmic, and implementation—have served
cognitive science well over the last 30 years. But the recent increase in the popularity of the …

The rationality principle postulates that decision-makers always choose the best action
available to them. It underlies most modern theories of decision-making. The principle does …

Modeling human cognition is challenging because there are infinitely many mechanisms
that can generate any given observation. Some researchers address this by constraining the …

We consider several key aspects of prediction in language comprehension: its
computational nature, the representational level (s) at which we predict, whether we use …

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the
brain deal successfully with the continual deluge of linguistic input? We argue that, to deal …

Human perceptual decisions are often described as optimal. Critics of this view have argued
that claims of optimality are overly flexible and lack explanatory power. Meanwhile …

Recent studies of probabilistic reasoning have postulated general-purpose inference
algorithms that can be used to answer arbitrary queries. These algorithms are memoryless …

Making good decisions requires thinking ahead, but the huge number of actions and
outcomes one could consider makes exhaustive planning infeasible for computationally …

How do people interact with computers? This fundamental question was asked by Card,
Moran, and Newell in 1983 with a proposition to frame it as a question about human …

This article presents the primitive elements theory of cognitive skills. The central idea is that
skills are broken down into primitive information processing elements that move and …