5 citations · 7 across the 3 of their papers we have counts for
3 papers
How to Learn from Risk: Explicit Risk-Utility Reinforcement Learning for Efficient and Safe Driving Strategies
Lukas M. Schmidt, Sebastian Rietsch, Axel Plinge +2
Autonomous driving has the potential to revolutionize mobility and is hence an active area of research. In practice, the behavior of autonomous vehicles must be acceptable, i.e., e…
Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series
Christoffer Loeffler, Wei-Cheng Lai, Bjoern Eskofier +3
The correct interpretation of convolutional models is a hard problem for time series data. While saliency methods promise visual validation of predictions for image and language pr…
An Introduction to Multi-Agent Reinforcement Learning and Review of its Application to Autonomous Mobility
Lukas M. Schmidt, Johanna Brosig, Axel Plinge +2
Many scenarios in mobility and traffic involve multiple different agents that need to cooperate to find a joint solution. Recent advances in behavioral planning use Reinforcement L…