Search Results for author:
Found 2 papers, 1 papers with code
Learning Optimal Advantage from Preferences and Mistaking it for Reward
Most recent work assumes that human preferences are generated based only upon the reward accrued within those segments, or their partial return.
Models of human preference for learning reward functions
We empirically show that our proposed regret preference model outperforms the partial return preference model with finite training data in otherwise the same setting.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
