8 citations · 14 across the 14 of their papers we have counts for
3 papers · 1 filter
Value Functions are Control Barrier Functions: Verification of Safe Policies using Control Theory
Daniel C. H. Tan, Fernando Acero, Robert McCarthy +2
Guaranteeing safe behaviour of reinforcement learning (RL) policies poses significant challenges for safety-critical applications, despite RL's generality and scalability. To addre…
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…
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,…