2 code implementations • 22 Jun 2020 • Patrick Hart, Alois Knoll
We show that graph neural networks are capable of handling scenarios with a varying number and order of vehicles during training and application.
2 code implementations • 20 Mar 2020 • Patrick Hart, Alois Knoll
If a policy can handle all counterfactual worlds well, it either has seen similar situations during training or it generalizes well and is deemed to be fit enough to be executed in the actual world.
no code implementations • 6 Mar 2020 • Patrick Hart, Leonard Rychly, Alois Knol
By storing the state-history during reinforcement learning, it can be used for constraint checking and the optimizer can account for interactions.
3 code implementations • 5 Mar 2020 • Julian Bernhard, Klemens Esterle, Patrick Hart, Tobias Kessler
As driving tests are costly and challenging scenarios are hard to find and reproduce, simulation is widely used to develop, test, and benchmark behavior models.
Multiagent Systems