Computer scientists have long recognized that naive implementations of algorithms often
result in a paralyzing degree of redundant computation. More sophisticated implementations …

Highlights•Structure learning may be key to inference from sparse data.•The psychological
and neural bases of structure learning are key challenges.•Normative accounts of structure …

The dilemma between information gathering (exploration) and reward seeking (exploitation)
is a fundamental problem for reinforcement learning agents. How humans resolve this …

What do infants know? How does the knowledge that they begin with prepare them for
learning about the particular physical, cultural, and social world in which they live? Answers …

Vision and learning have long been considered to be two areas of research linked only
distantly. However, recent developments in vision research have changed the conceptual …

How do people recognize and learn about complex functional structure? Taking inspiration
from other areas of cognitive science, we propose that this is achieved by harnessing …

Humans easily recognize object parts and their hierarchical structure by watching how they
move; they can then predict how each part moves in the future. In this paper, we propose a …

Identifying the structure of motion relations in the environment is critical for navigation,
tracking, prediction, and pursuit. Yet, little is known about the mental and neural …

Gestalt psychology is often criticized as lacking quantitative measurements and precise
mathematical models. While this is true of the early Gestalt school, today there are many …

“In What Makes Us Smart, Gershman turns his creative and fertile mind to writing a
compelling defense of the seeming impurities of our reason. He examines the broad and …