24 citations · 32 across the 9 of their papers we have counts for
3 papers · 1 filter
TEA: Trajectory Encoding Augmentation for Robust and Transferable Policies in Offline Reinforcement Learning
Batıkan Bora Ormancı, Phillip Swazinna, Steffen Udluft +1
In this paper, we investigate offline reinforcement learning (RL) with the goal of training a single robust policy that generalizes effectively across environments with unseen dyna…
Why long model-based rollouts are no reason for bad Q-value estimates
Philipp Wissmann, Daniel Hein, Steffen Udluft +1
This paper explores the use of model-based offline reinforcement learning with long model rollouts. While some literature criticizes this approach due to compounding errors, many p…
Model-based Offline Quantum Reinforcement Learning
Simon Eisenmann, Daniel Hein, Steffen Udluft +1
This paper presents the first algorithm for model-based offline quantum reinforcement learning and demonstrates its functionality on the cart-pole benchmark. The model and the poli…