Before revision:  what should the robot do when the human correction cannot be explained by the featuresit already has access to? Recent progress in deep Inverse Reinforcement Learning (IRL) suggests that the robot could fall back on demonstrations: ask the human for demonstrations of the task , and recover a reward defined over not just the known features, but also the raw state space.
After revision:  what should the robot do when the human correction cannot be explained by these features, recent work in deep Inverse Reinforcement Learning (IRL) suggests that the robot could fall back on demonstrations: ask the human for demonstrations of the task , and recover a reward defined over not just the known features, but also the raw state space.