3

Deep reinforcement learning of sequential action results in human-like optimization in a robotic arm controller

Predicting children's and adults' preferences in physical interactions via physics simulation

A large-scale comparison of cross-situational word learning models

One problem language learners face is extracting word meanings from scenes with many possible referents. Despite the ambiguity of individual situations, a large body of empirical work shows that people are able to learn cross-situationally when a …

Characterizing the object categories two children see and interact with in a dense dataset of naturalistic visual experience

What do infants and young children tend to see in their everyday lives? Relatively little work has examined the categories and objects that tend to be in the infant view during everyday experience, despite the fact that this knowledge is central to …

Detecting social information in a dense database of infants' natural visual experience

Exploring variation in infants' preference for infant-directed speech: Evidence from a multi-site study in Africa

Peekbank: Exploring children's word recognition through an open, large-scale repository for developmental eye-tracking data

The ability to rapidly recognize words and link them to referents in context is central to children's early language development. This ability, often called word recognition in the developmental literature, is typically studied in the …

Pragmatic communicators can overcome asymmetry by exploiting ambiguity

Active learners learn what simple samplers cannot: A Zipf-distributed vocabulary from limited data

Consistency and variability between cultures during toddlers' naturalistic play