3 papers
cs.LG2025
Safe Reinforcement Learning using Action Projection: Safeguard the Policy or the Environment?
Hannah Markgraf, Shambhuraj Sawant, Hanna Krasowski +3
Projection-based safety filters, which modify unsafe actions by mapping them to the closest safe alternative, are widely used to enforce safety constraints in reinforcement learnin…
cs.LG2025
Leveraging Analytic Gradients in Provably Safe Reinforcement Learning
Tim Walter, Hannah Markgraf, Jonathan Külz +1
The deployment of autonomous robots in safety-critical applications requires safety guarantees. Provably safe reinforcement learning is an active field of research that aims to pro…
cs.LG2025
PyTupli: A Scalable Infrastructure for Collaborative Offline Reinforcement Learning Projects
Hannah Markgraf, Michael Eichelbeck, Daria Cappey +3
Offline reinforcement learning (RL) has gained traction as a powerful paradigm for learning control policies from pre-collected data, eliminating the need for costly or risky onlin…