62 citations · 148 across the 29 of their papers we have counts for
3 papers · 1 filter
Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting
Nicolai Dorka, Tim Welschehold, Wolfram Burgard
Early stopping based on the validation set performance is a popular approach to find the right balance between under- and overfitting in the context of supervised learning. However…
Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning
Nicolai Dorka, Tim Welschehold, Joschka Boedecker +1
Accurate value estimates are important for off-policy reinforcement learning. Algorithms based on temporal difference learning typically are prone to an over- or underestimation bi…
Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning
Shengchao Yan, Tim Welschehold, Daniel Büscher +1
The transition from today's mostly human-driven traffic to a purely automated one will be a gradual evolution, with the effect that we will likely experience mixed traffic in the n…