Before revision:  This assumption fails to hold in all but the most isolated, controlled scenarios, reducing the ability to achieve the goal of empowering real end-users . Recent attempts to learn from sub-optimal demonstration leverage pairwise rankings through Preference-based Reinforcement Learning (PbRL) to infer a more optimal policy than the demonstration .
After revision:  This assumption fails to hold in all but the most isolated, controlled scenarios, reducing the ability to achieve the goal of empowering real end-users . Recent attempts to learn from sub-optimal demonstration leverage pairwise rankings and following the Luce-Shepard rule .