Sample-Based Rule Extraction for Explainable Reinforcement Learning. - Raphael C. Engelhardt; Moritz Lange; Laurenz Wiskott; Wolfgang Konen (LOD (1), 2022)

Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning. - Raphael C. Engelhardt; Ralitsa Raycheva; Moritz Lange; Laurenz Wiskott; Wolfgang Konen (LOD (2), 2023)

Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison. - Moritz Lange; Noah Krystiniak; Raphael C. Engelhardt; Wolfgang Konen; Laurenz Wiskott (LOD (2), 2023)

Iterative Oblique Decision Trees Deliver Explainable RL Models. - Raphael C. Engelhardt; Marc Oedingen; Moritz Lange; Laurenz Wiskott; Wolfgang Konen (Algorithms, 2023)

Exploring the Reliability of SHAP Values in Reinforcement Learning. - Raphael C. Engelhardt; Moritz Lange; Laurenz Wiskott; Wolfgang Konen (xAI (3), 2024)

Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks. - Moritz Lange; Raphael C. Engelhardt; Wolfgang Konen; Laurenz Wiskott (CoRR, 2024)

ChatGPT Code Detection: Techniques for Uncovering the Source of Code. - Marc Oedingen; Raphael C. Engelhardt; Robin Denz; Maximilian Hammer; Wolfgang Konen (CoRR, 2024)

Putting the Iterative Training of Decision Trees to the Test on a Real-World Robotic Task. - Raphael C. Engelhardt; Marcel J. Meinen; Moritz Lange; Laurenz Wiskott; Wolfgang Konen (CoRR, 2024)

Object-centric Denoising Diffusion Models for Physical Reasoning. - Moritz Lange; Raphael C. Engelhardt; Wolfgang Konen; Andrew Melnik; Laurenz Wiskott (CoRR, 2025)