@article{LiscaProdaniucGrauschopfetal.2021, author = {Lisca, Gheorghe and Prodaniuc, Cristian and Grauschopf, Thomas and Axenie, Cristian}, title = {Less Is More: Learning Insights From a Single Motion Sensor for Accurate and Explainable Soccer Goalkeeper Kinematics}, volume = {21}, journal = {IEEE Sensors Journal}, number = {18}, publisher = {IEEE}, address = {Piscataway}, issn = {1530-437X}, doi = {https://doi.org/10.1109/JSEN.2021.3094929}, pages = {20375 -- 20387}, year = {2021}, language = {en} } @inproceedings{SchiendorferLiscaOutafraoutetal.2024, author = {Schiendorfer, Alexander and Lisca, Gheorghe and Outafraout, Karima and Michailov, Lilia and K{\"a}tzel, Pascal and Felix, Rudolf}, title = {Gas Grid Copilot: Can a MORL Agent Assist a Dispatcher in Managing a Gas Grid?}, booktitle = {ECAI 2024: 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024), Proceedings}, editor = {Endriss, Ulle and Melo, Francisco S. and Bach, Kerstin and Bugar{\´i}n-Diz, Alberto and Alonso-Moral, Jos{\´e} M. and Barro, Sen{\´e}n and Heintz, Fredrik}, publisher = {IOS Press}, address = {Amsterdam}, isbn = {978-1-64368-548-9}, doi = {https://doi.org/10.3233/FAIA241025}, pages = {4443 -- 4446}, year = {2024}, abstract = {The distribution of fuel gases is undergoing major changes due to decarbonization efforts: Non-fossil gases such as biomethane or renewable hydrogen can lead to the reuse of existing gas infrastructure for gas storage, transport, and distribution to reduce greenhouse gas emissions while maintaining a high energy security. For safe and efficient operation, we propose Gas Grid Copilot (GGC) as a demonstrator of a multi-objective reinforcement learning agent that trains in a simulated gas grid environment to control a grid by modifying its inflow into a mass storage. Multiple, possibly conflicting reward signals are included. Their conflicts and synergies of rewards are analyzed using techniques from multi-criteria decision making, more specifically a conflict interaction matrix based on extended fuzzy logic. That way, dispatchers of a gas grid can explore the effects of reward prioritizations and their consequences safely.}, language = {en} } @inproceedings{BaschinBaschinBoeseltetal.2024, author = {Baschin, Anja and Baschin, Michelle and B{\"o}selt, Reinhard and Felix, Rudolf and Fernandez, Cesareo and Gehring, Sven and G{\"o}rtz, Alexander and Harpeng, Lars and Hei, Yuguang and Hildebrandt, Niclas and H{\"u}gging, Thomas and K{\"a}tzel, Pascal and Kolberg, Kristoffer-Robin and Kuoza, Leonid and Luzius, Lukas and Lisca, Gheorghe and Michailov, Lilia and Multhaup, Werner and Outafraout, Karima and Proch, Fabian and Schiendorfer, Alexander and Simmanek, Marcel and Streubel, Tom}, title = {Industrielle K{\"u}nstliche Intelligenz f{\"u}r sichere Gasnetze}, booktitle = {Tagungsband 18. Symposium Energieinnovation 2024}, publisher = {Technische Universit{\"a}t Graz}, address = {Graz}, url = {https://www.tugraz.at/events/eninnov2024/nachlese/download-beitraege/stream-a/\#c590685}, year = {2024}, language = {de} }