Forschungsinteressen
- Mechanistische Interpretierbarkeit von Machine Learning-Modellen, insbesondere Transformer-Architekturen
- Steuerung und Koordination von Multiagentensystemen mithilfe von Spieltheorie, Mechanism Design und Reinforcement Learning
Lebenslauf
| Seit 2024 | Wissenschaftlicher Mitarbeiter und Postdoc am Institut für Enterprise Systems |
|---|---|
| 2022 | Fulbright-Forschungsaufenthalt an der Texas A&M University (TAMU) |
| 2018–2024 | Wissenschaftlicher Mitarbeiter und Doktorand am Institut für Enterprise Systems |
| 2014–2017 | Consultant bei der TWS Partners AG |
| 2012–2014 | Master of Science Mathematics in Operations Research an der Technischen Universität München (TUM) |
| 2009–2012 | Bachelor of Science Mathematik an der Technischen Universität München (TUM) |
Publikationen
- Oesterle, M., Grams, T. und Bartelt, C. (2024). DRAMA at the PettingZoo: Dynamically restricted action spaces for multi-agent reinforcement learning frameworks. In , Proceedings of the 57th Annual Hawaii International Conference on System Sciences, HICSS 2024, Hilton Hawaiian Village Waikiki Beach Resort, Hawaii, USA, January 3–6, 2024 (S. 7810-7819). , Department of IT-Management, Shidler College of Business, University of Hawaii: Honolulu, HI.
- Oesterle, M., Grams, T., Bartelt, C. und Stuckenschmidt, H. (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 Multiagent Systems (S. 1492-1500). , International Foundation for Autonomous Agents and Multiagent Systems: Richland, SC.
- Rana, A., Oesterle, M. und Brinkmann, J. (2024). GOV-REK: Governed Reward Engineering Kernels for designing robust multi-agent reinforcement learning systems. In , AAMAS '24: proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (S. 2429-2431). , International Foundation for Autonomous Agents and Multiagent Systems: Richland, SC.
- Oesterle, M. und Sharon, G. (2023). Socially optimal non-discriminatory restrictions for continuous-action games. In , Proceedings of the 37th AAAI Conference of Artificial Intelligence. Vol. 10 (S. 11638-11646). , AAAI Press: Washington, DC.
- Oesterle, M. und Sharon, G. (2023). Socially optimal non-discriminatory restrictions for continuous-action games. In , KI 2023: Advances in Artificial Intelligence : 46th German Conference on AI, Berlin, Germany, September 26–29, 2023, Proceedings (S. 252–256). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
- Oesterle, M., Bartelt, C., Lüdtke, S. und Stuckenschmidt, H. (2022). Self-learning governance of black-box multi-agent systems. In , Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XV : International Workshop, COINE 2022, virtual event, May 9, 2022, revised selected papers (S. 73–91). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
- Pernpeintner, M. (2021). Self-learning governance of competitive multi-agent systems. In , Organic Computing : Doctoral Dissertation Colloquium 2020 (S. 47–63). Intelligent Embedded Systems, Kassel University Press: Kassel.
- Pernpeintner, M. (2021). Toward a self-learning governance loop for competitive multi-attribute MAS. In , AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems : Richland, SC, Virtual Event United Kingdom, May, 2021 (S. 1619-1621). , International Foundation for Autonomous Agents and Multiagent Systems: Richland, SC.
- Pernpeintner, M., Bartelt, C. und Stuckenschmidt, H. (2021). Governing black-box agents in competitive multi-agent systems. In , Multi-Agent Systems : 18th European Conference, EUMAS 2021, virtual event, June 28–29, 2021, revised selected papers (S. 19–36). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
- Pernpeintner, M. (2020). Achieving emergent governance in competitive multi-agent systems. In , AAMAS '20 : Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, Auckland, Nea Zealand, May 2020 (S. 2204-2206). , ACM Digital Library: New York, NY.
- Pernpeintner, M. (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 : proceedings (S. 231–233). , IEEE Computer Society Press: Piscataway, NJ.
- De Loera, J. A., Margulies, S., Pernpeintner, M., Riedl, E., Rolnick, D., Spencer, G., Stasi, D. und Swenson, J. (2015). Graph coloring ideals : Nullstellensatz certificates, Gröbner bases for chordal graphs, and hardness of Gröbner bases. In , ISSAC '15 : proceedings of the 2015 ACM International Symposium on Symbolic and Algebraic Computation : July 6–9, 2015, Bath, United Kingdom (S. 133–140). , ACM: New York, NY.
Betreute Abschlussarbeiten
- Governance for Sparse Multi-Agent Systems (Masterarbeit, 2023)
- Deep Reinforcement Learning in Obstacle Avoidance to Investigate Interval Restrictions on Action Spaces (Masterarbeit, 2022/
23) - Application and Evaluation of Multi-Agent Reinforcement Learning Approaches for the Coordinated Routing of Drones (Masterarbeit, 2021/
22) - Data Modeling And Processing for AI-based Governance of Competitive Multi-Agent Systems (Masterarbeit, 2020/
21) - Building an AI Agent for Strategic Interaction (Bachelorarbeit, 2019)
- Coverage-based Testing Improvement in the Domain of automated Driving – Utilizing unsupervised Selection of Traces in Field Data for Test Scenario Reconstruction (Masterarbeit, 2018/
19)