Tobias Huber M.Sc.

Research assistant
Chair for Human-Centered Artificial Intelligence
Phone: (+49)(0)821 – 598 2336
Room: 2015 (N)
Address: Universitätsstraße 6a, 86159 Augsburg

Research interest

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.



An introduction to explanation methods for reinforcement learning and their evaluation. Invited talk in the lecture series "Advanced Topics in AI and Robotics" at the University of Applied Sciences Bonn-Rhein-Sieg, 17.04.2023.

Presenting a demonstrator on Explainable Artificial Intelligence at the opening of the "KI-Erlebnisraums Halle 43". Augsburg, 19.06.2023


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


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.


  • WS23/24: Partical Course Game Development

  • SS23 Game Development

  • WS22/23: Partical Course Game Development

  • SS22: Game Development

  • WS21/22: Partical Course Game Development

  • SS21: Game Development

  • WS20/21: Partical Course Game Development

  • SS20: Game Development

  • WS 19/20: Partical Course Game Development

  • SS 19: Game Development

  • WS 18/19: Partical Course Game Development

Insights into final projects

On the courses' website you can see and even play projects from the game programming lectures.






Other lectures I am involved with:

Supervised theses

Master’s Thesis

  • Deep Reinforcement Learning with MuZero: Theoretical Foundations, Variants, and Implementation for a Collaborative Game (2023)

  • 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

  • Explaining the Global Behavior of Deep Reinforcement Learning Agents by Combining T-SNE and Policy Summarization (2023)
  • 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)

Voluntary Activities

Since the end of 2022, 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.


2023 | 2022 | 2021 | 2020 | 2019 | 2018


Anan Schütt, Tobias Huber, Ilhan Aslan and Elisabeth André. 2023. Fast dynamic difficulty adjustment for intelligent tutoring systems with small datasets.
PDF | BibTeX | RIS | URL

Tobias Huber, Maximilian Demmler, Silvan Mertes, Matthew Olson and Elisabeth Andrè. 2023. GANterfactual-RL: understanding reinforcement learning agents' strategies through visual counterfactual explanations. DOI: 10.5555/3545946.3598751
BibTeX | RIS | DOI | URL

Yael Septon, Tobias Huber, Elisabeth André and Ofra Amir. 2023. Integrating policy summaries with reward decomposition for explaining reinforcement learning agents. DOI: 10.1007/978-3-031-37616-0_27
BibTeX | RIS | DOI


Silvan Mertes, Christina Karle, Tobias Huber, Katharina Weitz, Ruben Schlagowski and Elisabeth André. in press. Alterfactual explanations: the relevance of irrelevance for explaining AI systems. DOI: 10.48550/arXiv.2207.09374
BibTeX | RIS | DOI

Tobias Huber, Benedikt Limmer and Elisabeth André. 2022. Benchmarking perturbation-based saliency maps for explaining Atari agents. DOI: 10.3389/frai.2022.903875
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Pooja Prajod, Dominik Schiller, Tobias Huber and Elisabeth André. 2022. Do deep neural networks forget facial action units? - Exploring the effects of transfer learning in health related facial expression recognition. DOI: 10.1007/978-3-030-93080-6_16
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Silvan Mertes, Tobias Huber, Katharina Weitz, Alexander Heimerl and Elisabeth André. 2022. GANterfactual - counterfactual explanations for medical non-experts using generative adversarial learning. DOI: 10.3389/frai.2022.825565
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Pooja Prajod, Tobias Huber and Elisabeth André. 2022. Using explainable AI to identify differences between clinical and experimental pain detection models based on facial expressions. DOI: 10.1007/978-3-030-98358-1_25
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Tobias Huber, Silvan Mertes, Stanislava Rangelova, Simon Flutura and Elisabeth André. 2021. Dynamic difficulty adjustment in virtual reality exergames through experience-driven procedural content generation. DOI: 10.1109/ssci50451.2021.9660086
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Tobias Huber, Katharina Weitz, Elisabeth André and Ofra Amir. 2021. Local and global explanations of agent behavior: integrating strategy summaries with saliency maps. DOI: 10.1016/j.artint.2021.103571
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Katharina Weitz, Dominik Schiller, Ruben Schlagowski, Tobias Huber and Elisabeth André. 2020. "Let me explain!": exploring the potential of virtual agents in explainable AI interaction design. DOI: 10.1007/s12193-020-00332-0
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Simon Flutura, Andreas Seiderer, Tobias Huber, Katharina Weitz, Ilhan Aslan, Ruben Schlagowski, Elisabeth André and Joachim Rathmann. 2020. Interactive machine learning and explainability in mobile classification of forest-aesthetics. DOI: 10.1145/3411170.3411225
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Dominik Schiller, Tobias Huber, Michael Dietz and Elisabeth André. 2020. Relevance-based data masking: a model-agnostic transfer learning approach for facial expression recognition. DOI: 10.3389/fcomp.2020.00006
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Klaus Weber, Lukas Tinnes, Tobias Huber, Alexander Heimerl, Eva Pohlen, Marc-Leon Reinecker and Elisabeth André. 2020. Towards demystifying subliminal persuasiveness: using XAI-techniques to highlight persuasive markers of public speeches. DOI: 10.1007/978-3-030-51924-7_7
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Katharina Weitz, Dominik Schiller, Ruben Schlagowski, Tobias Huber and Elisabeth André. 2019. "Do you trust me?" Increasing user-trust by integrating virtual agents in explainable AI interaction design. DOI: 10.1145/3308532.3329441
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Tobias Huber, Dominik Schiller and Elisabeth André. 2019. Enhancing explainability of deep reinforcement learning through selective layer-wise relevance propagation. DOI: 10.1007/978-3-030-30179-8_16
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Stanislava Rangelova, Simon Flutura, Tobias Huber, Daniel Motus and Elisabeth André. 2019. Exploration of physiological signals using different locomotion techniques in a VR adventure game. DOI: 10.1007/978-3-030-23560-4_44
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Dominik Schiller, Tobias Huber, Florian Lingenfelser, Michael Dietz, Andreas Seiderer and Elisabeth André. 2019. Relevance-based feature masking: improving neural network based whale classification through explainable artificial intelligence. DOI: 10.21437/interspeech.2019-2707
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Tobias Huber. 2018. Tiefes bestärkendes Lernen: Grundlagen, Approximationseigenschaft und Implementierung multimodaler Erklärungen.
PDF | BibTeX | RIS