PHIRL: Aligning Learned Rewards with Task Progress for Inverse Reinforcement Learning
Progress-Heuristicized Inverse Reinforcement Learning (PHIRL), a data-efficient framework that learns robust reward functions by jointly leveraging demonstrations and feedback, uses progress, a feedback modality that describes cumulative task completion.
Hang Yu, James Staley, Cheng-Xi Tsou et al.
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