Constructing Abstraction Hierarchies for Robust, Real-Time Control
Technical Report,15 Jan 2017,14 Jan 2020
BROWN UNIVERSITY PROVIDENCE United States
Pagination or Media Count:
This project primarily focused on the theoretical principles underlying which high-level actions an agent should build, and data-efficient algorithms for learning those high-level actions from interaction with an agents environment. The projected funded a single PhD student for three years, and resulted in 5 publications at top-tier, highly-refereed international conferences, and 3 additional publications either in preparation or currently under review. The report describes these research results and draws appropriate conclusions.