Timo Sievernich

Uncertainty-Aware Model-Based Offline Reinforcement Learning for Automated Driving

Offline reinforcement learning (RL) provides a framework for learning decision-making from offline data and therefore constitutes a promising approach for real-world applications such as automated driving (AD). Especially in safety-critical applications, interpretability and transferability are cruc