91 citations · 91 across the 5 of their papers we have counts for
4 papers · 1 filter
Revisiting Safe Exploration in Safe Reinforcement learning
David Eckel, Baohe Zhang, Joschka Bödecker
Safe reinforcement learning (SafeRL) extends standard reinforcement learning with the idea of safety, where safety is typically defined through the constraint of the expected cost…
Constrained Reinforcement Learning for Safe Heat Pump Control
Baohe Zhang, Lilli Frison, Thomas Brox +1
Constrained Reinforcement Learning (RL) has emerged as a significant research area within RL, where integrating constraints with rewards is crucial for enhancing safety and perform…
Constrained Reinforcement Learning with Smoothed Log Barrier Function
Baohe Zhang, Yuan Zhang, Lilli Frison +2
Reinforcement Learning (RL) has been widely applied to many control tasks and substantially improved the performances compared to conventional control methods in many domains where…
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Jack Parker-Holder, Raghu Rajan, Xingyou Song +9
The combination of Reinforcement Learning (RL) with deep learning has led to a series of impressive feats, with many believing (deep) RL provides a path towards generally capable a…