124 citations · 297 across the 22 of their papers we have counts for
1 paper · 2 filters
L. L. Ankile, B. S. Ham, K. Mao +4
When assisting human users in reinforcement learning (RL), we can represent users as RL agents and study key parameters, called \emph{user traits}, to inform intervention design. W…