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20192023
most citedDexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks

17 citations · 22 across the 10 of their papers we have counts for

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2 papers · 1 filter

cs.LG2023

Improving Behavioural Cloning with Positive Unlabeled Learning

Qiang Wang, Robert McCarthy, David Cordova Bulens +6

Learning control policies offline from pre-recorded datasets is a promising avenue for solving challenging real-world problems. However, available datasets are typically of mixed q…

cs.LG2021★ 2 cited

Imaginary Hindsight Experience Replay: Curious Model-based Learning for Sparse Reward Tasks

Robert McCarthy, Qiang Wang, Stephen J. Redmond

Model-based reinforcement learning is a promising learning strategy for practical robotic applications due to its improved data-efficiency versus model-free counterparts. However,…