4 citations · 6 across the 7 of their papers we have counts for
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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,…