Adaptive Training Systems for Human-Robot Interaction

Abstract: Future industrial development will depend on specialized human-robot teams that can quickly adapt to new tasks. In this dissertation, I present a framework for adaptive training systems inspired by foundational work in intelligent tutoring systems. Using two task domains, I illustrate how formal analysis methods can be used for automatic assessment; these results can be used to create formative feedback using generative AI. I will finish by discussing future opportunities for improving adaptive training systems.

Bio: Emily Jensen is a PhD Candidate in Computer Science and Cognitive Science. She received a BA in Cognitive Science and a BS in Mathematics at Case Western Reserve University. While at CU Boulder, Emily was an active member in CSGSA and GPSG. She was awarded a Journeyman Fellowship at the U.S. Army Research Laboratory. Emily will be joining Franklin & Marshall College as an Assistant Professor of Computer Science in the fall.