Abstract
Our research aims to computationally model mechanisms of human social learning in order to build robots and other machines that are intuitive for people to teach. We take Machine Learning interactions and redesign interfaces and algorithms to support the collection of learning input from end users instead of ML experts. This talk covers results on building models of reciprocal interactions, high-level task goal learning, low-level skill learning, and active learning interactions using anthropomorphic robot platforms.