I argue that the evolution of our life history, with its distinctively long, protected human
childhood, allows an early period of broad hypothesis search and exploration, before the …

In coming to understand the world—in learning concepts, acquiring language, and gras**
causal relations—our minds make inferences that appear to go far beyond the data …

Humans spontaneously organize a continuous experience into discrete events and use the
learned structure of these events to generalize and organize memory. We introduce the …

A key problem in statistical modeling is model selection, that is, how to choose a model at an
appropriate level of complexity. This problem appears in many settings, most prominently in …

For over 200 years, philosophers and mathematicians have be en using probability theory to
describe human cognition. While the theory of prob abilities was first developed as a means …

The scope of human learning and development poses a radical challenge for cognitive
science. We propose that developmental theories can address this challenge by adopting …

Meaning is a fundamental component of nearly all aspects of human cognition, but formal
models of semantic memory have classically lagged behind many other areas of cognition …

We present an introduction to Bayesian inference as it is used in probabilistic models of
cognitive development. Our goal is to provide an intuitive and accessible guide to the what …

Both cognitive and educational psychology literature strive to investigate human category
and concept learning. However, both literatures focus on different phenomena and often use …

Effective reinforcement learning hinges on having an appropriate state representation. But
where does this representation come from? We argue that the brain discovers state …