most citedMonte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations

5 citations · 5 across the 1 of their papers we have counts for

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1 paper

cs.LG2022★ 5 cited

Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations

Albert Wilcox, Ashwin Balakrishna, Jules Dedieu +3

Providing densely shaped reward functions for RL algorithms is often exceedingly challenging, motivating the development of RL algorithms that can learn from easier-to-specify spar…