Dustin Lehmann
Photo: SCIoI
Dustin Lehmann graduated in Aerospace Engineering at TU Berlin, focusing on control theory. In his SCIoI doctoral project, he worked on applying control theory concepts to multi-agent learning problems. In particular, he focused on using learning control approaches as well as distributed and network control concepts.
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Lehmann
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19928
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Lehmann, D., Drebinger, P., Seel, T., & Raisch, J. (2023). Data-Driven Dynamic Input Transfer for Learning Control in Multi-Agent Systems with Heterogeneous Unknown Dynamics. 2023 62nd IEEE Conference on Decision and Control (CDC), 2358–2365. https://doi.org/10.1109/CDC49753.2023.10383433
Meindl, M., Lehmann, D., & Seel, T. (2022). Bridging Reinforcement Learning and Iterative Learning Control: Autonomous Motion Learning for Unknown, Nonlinear Dynamics. Frontiers in Robotics and AI, 9, 793512. https://doi.org/10.3389/frobt.2022.793512
Meindl, M., Molinari, F., Lehmann, D., & Seel, T. (2022). Collective Iterative Learning Control: Exploiting Diversity in Multi-Agent Systems for Reference Tracking Tasks. IEEE Transactions on Control Systems Technology, 30(4), 1390–1402. https://doi.org/10.1109/TCST.2021.3109646
