My research focuses on the explainability of Artificial Intelligence and Reinforcement Learning in particular.

I find it fascinating how Reinforcement Learning algorithms can independently develop strategies based only on observations and rewards. In some cases, the agents even develop new strategies that even humans have not yet considered ( e.g. by the chess computer AlphaZero). However, since only the goal of the agents is defined, it is often not clear what exactly the learned strategies look like. This is exacerbated by the use of modern machine learning techniques, which achieve considerable success but are also very opaque.

The goal of my research is to develop new algorithms that make the behaviour of intelligent agents explainable to users and thus facilitate the cooperation between humans and computers.

2022

Was Pacman denkt – Wie künstliche Intelligenz das Spielen lernt. Talk at the  long night of sciences, Augsburg, 16.07.2022, Slides .

2021

Explainable deep Reinforcement Learning. Invited talk in the CSL Machine Learning Reading Club of the Computational Science Lab (CSL) at the University of Hohenheim, 02.02.2021, Slides .

Since the winter semester 18/19 I am one of the main lecturers for the courses Game Development and Partical Course Game Development.

Other lectures I am involved with:

•  WS22/23: Reinforcement Learning

• WS21/22: Reinforcement Learning

Master’s Thesis

• Generating Counterfactual Explanations for Atari Agents via Generative Adversarial Networks (2022)

• Design und Implementierung einer Virtual-Reality-Umgebung zum Testen des impliziten Lernens von motorischen sequentiellen Bewegungen (2021, Link)

• Exploring an Explainable Reinforcement Learning Design for a Self Learning American Football Simulation (2020)
• Implementierung und Vergleich verschiedener Salienz-Karten Algorithmen für tiefes bestärkendes Lernen (2019)

Bachelor’s Thesis

• Using Reinforcement Learning to facilitate Implicit Learning in a VR Sports Simulation (2021)
• Understanding Subliminal Persuasive Body Language in Political Speeches via ExplainableArtificial Intelligence (2021)
• Verbinden von Belohnungs-Zerlegung und Strategie-Zusammenfassung für erklärbares Bestärkendes Lernen (2021)

• Implementation and Comparison of Occlusion-based Explainable Artificial Intelligence Methods (2020, Link)

I was reviewer for the following conferences and journals:

• AAAI 2022: AAAI Conference on Artificial Intelligence
• CHI 2022: ACM Conference on Human Factors in Computing Systems
• IJCAI 2022 Workshop on Explainable Artificial Intelligence (XAI)

• Multimedia Tools and Applications

• Programme Committee member: AAAI 2022: AAAI Conference on Artificial Intelligence
• Programme Committee member and Session Chair:  IJCAI 2022 Workshop on Explainable Artificial Intelligence (XAI)
• Programme Committee member:  ECAI 2023: European Conference on Artificial Intelligence

Since 2023, I am speaker of the Advisory Board for Young Scientists of the Gesellschaft für Informatik (GI), the largest professional society for computer science in the German-speaking world.