What do we want from machine intelligence? We envision machines that are not just tools
for thought but partners in thought: reasonable, insightful, knowledgeable, reliable and …

After growing up together, and mostly growing apart in the second half of the 20th century,
the fields of artificial intelligence (AI), cognitive science, and neuroscience are reconverging …

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 …

In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly
understood. Although most researchers agree that mental effort is aversive and stems from …

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

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

Many contemporary accounts of human reasoning assume that the mind is equipped with
multiple heuristics that could be deployed to perform a given task. This raises the question of …

The human brain has the impressive capacity to adapt how it processes information to high-
level goals. While it is known that these cognitive control skills are malleable and can be …

Artificial intelligence systems use an increasing amount of computation and data to solve
very specific problems. By contrast, human minds solve a wide range of problems using a …

We present an information-theoretic framework for solving global black-box optimization
problems that also have black-box constraints. Of particular interest to us is to efficiently …