M.Sc. Johannes Fischer
- Wissenschaftlicher Mitarbeiter
- Raum: 039
- Tel.: +49 721 608-48760
- johannes fischer ∂kit edu
Karlsruher Institut für Technologie (KIT)
Institut für Mess- und Regelungstechnik
Engler-Bunte-Ring 21
Gebäude 40.32
D-76131 Karlsruhe
Forschung
- Decision Making under Uncertainty
- Inverse Reinforcement Learning from Human Behavior
- Stochastic Optimization
Lehre
- Übungen zu Grundlagen der Mess- und Regelungstechnik
- Tutorial for Measurement and Control Systems
- Übungen zu Regelungstechnik und Systemdynamik
Veröffentlichungen
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Test-Driven Inverse Reinforcement Learning Using Scenario-Based Testing
Fischer, J.; Werling, M.; Lauer, M.; Stiller, C.
2024. 2024 IEEE Intelligent Vehicles Symposium (IV), Jeju, 2nd-5th June 2024, 827–834, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IV55156.2024.10588652 -
Safety Reinforced Model Predictive Control (SRMPC): Improving MPC with Reinforcement Learning for Motion Planning in Autonomous Driving
Fischer, J.; Steiner, M.; Tas, Ö. S.; Stiller, C.
2024. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ITSC57777.2023.10422605 -
Physics-Informed Reinforcement Learning for Automated Merging in Dense Traffic
Fischer, J.; Trofimov, A.; Stiller, C.
2023. 15. Workshop Fahrerassistenz Und Automatisiertes Fahren (FAS), 43–51, Uni-DAS -
Gap Approaching Intelligent Driver Model for Interactive Simulation of Merging Scenarios
Fischer, J.; Bührle, E.; Stiller, C.
2023. 2023 IEEE Intelligent Vehicles Symposium (IV), 1–8, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IV55152.2023.10186618 -
SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments
Jamgochian, A.; Buehrle, E.; Fischer, J.; Kochenderfer, M. J.
2023. 2023 IEEE International Conference on Robotics and Automation (ICRA), 29th May - 02nd June 2023, London, 1530 – 1536, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRA48891.2023.10161449 -
Guiding Belief Space Planning with Learned Models for Interactive Merging
Fischer, J.; Buhrle, E.; Kamran, D.; Stiller, C.
2022. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2542–2549, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ITSC55140.2022.9922488 -
A Modern Perspective on Safe Automated Driving for Different Traffic Dynamics Using Constrained Reinforcement Learning
Kamran, D.; Simão, T. D.; Yang, Q.; Ponnambalam, C. T.; Fischer, J.; Spaan, M. T. J.; Lauer, M.
2022. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 4017–4023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ITSC55140.2022.9921907 -
Interaction-Aware Game-Theoretic Motion Planning for Automated Vehicles using Bi-level Optimization
Burger, C.; Fischer, J.; Bieder, F.; Tas, O. S.; Stiller, C.
2022. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 3978–3985, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ITSC55140.2022.9922600 -
Sampling-Based Inverse Reinforcement Learning Algorithms with Safety Constraints
Fischer, J.; Eyberg, C.; Werling, M.; Lauer, M.
2021. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prag, CZ, September 27 - October 1, 2021, 791 – 798, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IROS51168.2021.9636672 -
Minimizing Safety Interference for Safe and Comfortable Automated Driving with Distributional Reinforcement Learning
Kamran, D.; Engelgeh, T.; Busch, M.; Fischer, J.; Stiller, C.
2021. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1236 – 1243, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IROS51168.2021.9636847 -
Information particle filter tree: An online algorithm for POMDPs with belief-based rewards on continuous domains
Fischer, J.; Taş, Ö. Ş.
2021. 37th International Conference on Machine Learning (ICML 2020) : online, 13-18 July 2020. Part 5. Ed.: H. Daumé, 3158–3168, Curran Associates