41 citations · 63 across the 6 of their papers we have counts for
3 papers · 1 filter
Benchmarking Offline Reinforcement Learning on Real-Robot Hardware
Nico Gürtler, Sebastian Blaes, Pavel Kolev +5
Learning policies from previously recorded data is a promising direction for real-world robotics tasks, as online learning is often infeasible. Dexterous manipulation in particular…
Hierarchical Reinforcement Learning with Timed Subgoals
Nico Gürtler, Dieter Büchler, Georg Martius
Hierarchical reinforcement learning (HRL) holds great potential for sample-efficient learning on challenging long-horizon tasks. In particular, letting a higher level assign subgoa…
Direct Advantage Estimation
Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz +1
The predominant approach in reinforcement learning is to assign credit to actions based on the expected return. However, we show that the return may depend on the policy in a way w…