From “Thumbs Up” to “10 out of 10”: Reconsidering Scalar Feedback in Interactive Reinforcement Learning
Hang Yu,Reuben M. Aronson,Katherine H. Allen,Elaine Schaertl Short,Hang Yu,Reuben M. Aronson,Katherine H. Allen,Elaine Schaertl Short
Learning from human feedback is an effective way to improve robotic learning in exploration-heavy tasks. Compared to the wide application of binary human feedback, scalar human feedback has been used less because it is believed to be noisy and unstable. In this paper, we compare scalar and binary feedback, and demonstrate that scalar feedback benefits learning when properly handled. We collected b...
