most citedProvably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments

2 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

stat.ML2025★ 1 cited

Multi-Objective Causal Bayesian Optimization

Shriya Bhatija, Paul-David Zuercher, Jakob Thumm +1

In decision-making problems, the outcome of an intervention often depends on the causal relationships between system components and is highly costly to evaluate. In such settings,…

cs.RO2022★ 2 cited

Provably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments

Jakob Thumm, Matthias Althoff

Deep reinforcement learning (RL) has shown promising results in the motion planning of manipulators. However, no method guarantees the safety of highly dynamic obstacles, such as h…