Axel Brunnbauer

Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars.

2021 · arXiv (Cornell University)

Despite the rich theoretical foundation of model-based deep reinforcement learning (RL) agents, their effectiveness in real-world robotics-applications is less studied and understood. In this paper, we, therefore, investigate how such agents generalize to real-world autonomous-vehicle …

Scalable Offline Reinforcement Learning for Mean Field Games

2024 · arXiv (Cornell University)

Reinforcement learning algorithms for mean-field games offer a scalable framework for optimizing policies in large populations of interacting agents. Existing methods often depend on online interactions or access to system dynamics, limiting their practicality in …