3 papers
cs.RO2025
CHEQ-ing the Box: Safe Variable Impedance Learning for Robotic Polishing
Emma Cramer, Lukas Jäschke, Sebastian Trimpe
Robotic systems are increasingly employed for industrial automation, with contact-rich tasks like polishing requiring dexterity and compliant behaviour. These tasks are difficult t…
cs.LG2024
Contextualized Hybrid Ensemble Q-learning: Learning Fast with Control Priors
Emma Cramer, Bernd Frauenknecht, Ramil Sabirov +1
Combining Reinforcement Learning (RL) with a prior controller can yield the best out of two worlds: RL can solve complex nonlinear problems, while the control prior ensures safer e…
cs.LG2024
Combining Automated Optimisation of Hyperparameters and Reward Shape
Julian Dierkes, Emma Cramer, Holger H. Hoos +1
There has been significant progress in deep reinforcement learning (RL) in recent years. Nevertheless, finding suitable hyperparameter configurations and reward functions remains c…