LAUSR

Learning Potential in Subgoal-Based Reward Shaping

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2 Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3246267

Abstract: Human knowledge can reduce the number of iterations required to learn in reinforcement learning. Though the most common approach uses trajectories, it is difficult to acquire them in certain domains. Subgoals, which are intermediate states,… read more here.

Keywords: based reward; reward shaping; learned potential; subgoal based ... See more keywords