1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
Comparing Model-free and Model-based Algorithms for Offline Reinforcement Learning
Phillip Swazinna, Steffen Udluft, Daniel Hein +1
Offline reinforcement learning (RL) Algorithms are often designed with environments such as MuJoCo in mind, in which the planning horizon is extremely long and no noise exists. We…
cs.LG2021
Behavior Constraining in Weight Space for Offline Reinforcement Learning
Phillip Swazinna, Steffen Udluft, Daniel Hein +1
In offline reinforcement learning, a policy needs to be learned from a single pre-collected dataset. Typically, policies are thus regularized during training to behave similarly to…