Concept learning as motor program induction: A large-scale empirical study

Human concept learning is particularly impressive in two respects: the internal structure of concepts can be representationally rich, and yet the very same concepts can also be learned from just a few examples. Several decades of research have dramatically advanced our understanding of these two aspects of concepts. While the richness and speed of concept…

Human-level concept learning through probabilistic program induction

People learning new concepts can often generalize successfully from just a single example, yet machine learning algorithms typically require tens or hundreds of examples to perform with similar accuracy. People can also use learned concepts in richer ways than conventional algorithms—for action, imagination, and explanation. We present a computational model that captures these human learning…

Robots That Stereotype: Creating and Using Categories of People for Human-Robot Interaction

Psychologists note that humans use categories to simplify and speed the process of person perception. Applications that require a robot to interact with a variety of different people will demand the creation of stereotypes representing different categories of people. This article presents a method for stereotype learning and usage by a robot. Both robot and…