4 papers
Addressing Trust in AI Systems through Education: A Didactic Perspective
Pierre Haritz, Hendrik Krone, Thomas Liebig
Machine learning (ML) education faces two persistent and connected obstacles: many educational tools present ML as an opaque black box, which leaves learners with a superficial und…
ICE-T: A Multi-Faceted Concept for Teaching Machine Learning
Hendrik Krone, Pierre Haritz, Thomas Liebig
The topics of Artificial intelligence (AI) and especially Machine Learning (ML) are increasingly making their way into educational curricula. To facilitate the access for students,…
Using Petri Nets as an Integrated Constraint Mechanism for Reinforcement Learning Tasks
Timon Sachweh, Pierre Haritz, Thomas Liebig
The lack of trust in algorithms is usually an issue when using Reinforcement Learning (RL) agents for control in real-world domains such as production plants, autonomous vehicles,…
Enhancing Safety for Autonomous Agents in Partly Concealed Urban Traffic Environments Through Representation-Based Shielding
Pierre Haritz, David Wanke, Thomas Liebig
Navigating unsignalized intersections in urban environments poses a complex challenge for self-driving vehicles, where issues such as view obstructions, unpredictable pedestrian cr…