60 citations · 155 across the 7 of their papers we have counts for
4 papers · 1 filter
Learning Reward Models for Cooperative Trajectory Planning with Inverse Reinforcement Learning and Monte Carlo Tree Search
Karl Kurzer, Matthias Bitzer, J. Marius Zöllner
Cooperative trajectory planning methods for automated vehicles can solve traffic scenarios that require a high degree of cooperation between traffic participants. However, for coop…
Parallelization of Monte Carlo Tree Search in Continuous Domains
Karl Kurzer, Christoph Hörtnagl, J. Marius Zöllner
Monte Carlo Tree Search (MCTS) has proven to be capable of solving challenging tasks in domains such as Go, chess and Atari. Previous research has developed parallel versions of MC…
Accelerating Cooperative Planning for Automated Vehicles with Learned Heuristics and Monte Carlo Tree Search
Karl Kurzer, Marcus Fechner, J. Marius Zöllner
Efficient driving in urban traffic scenarios requires foresight. The observation of other traffic participants and the inference of their possible next actions depending on the own…
Adaptive Behavior Generation for Autonomous Driving using Deep Reinforcement Learning with Compact Semantic States
Peter Wolf, Karl Kurzer, Tobias Wingert +2
Making the right decision in traffic is a challenging task that is highly dependent on individual preferences as well as the surrounding environment. Therefore it is hard to model…