• Michael Oesterle, Patrick Blöbaum, Atalanti A. Mastakouri, Elke Kirschbaum (2025). Beyond Single-Feature Importance with ICECREAM. To appear in: Proceedings of the Fourth Conference on Causal Learning and Reasoning (CLeaR 2025).

  • Daniel Balcells, Benjamin Lerner, Michael Oesterle, Ediz Ucar, Stefan Heimersheim (2024). Evolution of SAE Features Across Layers in LLMs. In: Proceedings of the 2nd Workshop on Attributing Model Behavior at Scale (ATTRIB 2024 @ NeurIPS).

  • Michael Oesterle (2024). Self-Learning Restriction-Based Governance of Multi-Agent Systems. Doctoral Thesis.

  • Michael Oesterle, Tim Grams, Christian Bartelt and Heiner Stuckenschmidt (2024). RAISE the Bar: Restriction of Action Spaces for Improved Social Welfare and Equity in Traffic Management. In: Proceedings of the 23rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2024).

  • Michael Oesterle, Tim Grams and Christian Bartelt (2024). DRAMA at the PettingZoo: Dynamically Restricted Action Spaces for Multi-Agent Reinforcement Learning Frameworks. In: Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS 2024).

  • Michael Oesterle and Guni Sharon (2023). Socially Optimal NonDiscriminatory Restrictions for Continuous-Action Games. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI 2023).

  • Michael Oesterle, Christian Bartelt, Stefan Lüdtke and Heiner Stuckenschmidt (2022). Self-learning Governance of Black-Box Multi-Agent Systems. In: Proceedings of the International Workshop on Coordination, Organizations, Institutions, Norms and Ethics for Governance of Multi-Agent Systems (COINE 2022).

  • Michael Pernpeintner, Christian Bartelt and Heiner Stuckenschmidt (2021). Governing Black-Box Agents in Competitive Multi-Agent Systems. In: Proceedings of the 18th European Conference on Multi-Agent Systems (EUMAS 2021).

  • Michael Pernpeintner (2021). Self-Learning Governance of Competitive Multi-Agent Systems. In: Organic Computing Doctoral Dissertation Colloquium (OCDDC 2020).

  • Michael Pernpeintner (2021). Toward a Self-Learning Governance Loop for Competitive Multi-Attribute MAS (Extended Abstract). In: Proceedings of the 20th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2021).

  • Michael Pernpeintner (2020). Achieving Emergent Governance in Competitive Multi-Agent Systems (Doctoral Consortium). In: Proceedings of the 19th International Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2020).

  • Michael Pernpeintner (2019). Collaboration as an Emergent Property of Self-Organizing Software Systems. In: 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W 2019).

  • Jesus Antonio De Loera, Susan Margulies, Michael Pernpeintner, Eric Riedl, David Rolnick, Gwen Spencer, Despina Stasi and Jon Swenson (2015). Graph coloring ideals: Nullstellensatz Certificates, Gröbner Bases for Chordal Graphs, and Hardness of Gröbner Bases. In: Proceedings of the 2015 ACM International Symposium on Symbolic and Algebraic Computation (ISSAC 2015).