1 citations · 1 across the 3 of their papers we have counts for
4 papers
dtControl2+: Trading Optimality for Explainability in MDPs via Decision Trees
Tereza Kinská, Jan KÅetÃnský, Tobias Meggendorfer +2
Over the past decade, decision trees have been used to represent controllers (a.k.a. policies) in an explainable way, with dtControl2 as a current state-of-the-art tool. However, f…
Explainably Safe Reinforcement Learning
Sabine Rieder, Stefan Pranger, Debraj Chakraborty +2
Trust in a decision-making system requires both safety guarantees and the ability to interpret and understand its behavior. This is particularly important for learned systems, whos…
Edge Case Detection in Automated Driving: Methods, Challenges, and Future Directions
Saeed Rahmani, Sabine Rieder, Erwin de Gelder +6
Automated vehicles (AVs) promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains challenging, particularly due…
Gaussian-Based and Outside-the-Box Runtime Monitoring Join Forces
Vahid Hashemi, Jan KÅetÃnský, Sabine Rieder +2
Since neural networks can make wrong predictions even with high confidence, monitoring their behavior at runtime is important, especially in safety-critical domains like autonomous…