Explainable Reinforcement Learning: A Survey E Puiutta, EMSP Veith arXiv preprint arXiv:2005.06247, 2020 | 320 | 2020 |
Adversarial Resilience Learning—Towards Systemic Vulnerability Analysis for Large and Complex Systems L Fischer, JM Memmen, E Veith, M Tröschel The Ninth International Conference on Smart Grids, Green Communications and …, 2019 | 29 | 2019 |
Analyzing cyber-physical systems from the perspective of artificial intelligence EMSP Veith, L Fischer, M Tröschel, A Nieße Proceedings of the 2019 International Conference on Artificial Intelligence …, 2019 | 27 | 2019 |
Flexibility management and provision of balancing services with battery-electric automated guided vehicles in the Hamburg container terminal Altenwerder S Holly, A Nieße, M Tröschel, L Hammer, C Franzius, V Dmitriyev, ... Energy Informatics 3, 1-20, 2020 | 26 | 2020 |
Gapi: A g-lab application-to-network interface F Liers, T Volkert, D Martin, H Backhaus, H Wippel, E Veith, A Siddiqui, ... 11th Würzburg Workshop on IP: Joint ITG and Euro-NF Workshop" Visions of …, 2011 | 21 | 2011 |
Universal smart grid agent for distributed power generation management E Veith Logos Verlag Berlin, 2017 | 18 | 2017 |
The spectrum of proactive, resilient multi-microgrid scheduling: A systematic literature review MH Spiegel, EMSP Veith, TI Strasser Energies 13 (17), 4543, 2020 | 17 | 2020 |
Large scale rollout of smart grid services F Kintzler, T Gawron-Deutsch, S Cejka, J Schulte, M Uslar, EMSP Veith, ... 2018 Global Internet of Things Summit (GIoTS), 1-7, 2018 | 14 | 2018 |
A description language for communication services of future network architectures R Khondoker, EMSP Veith, P Mueller 2011 International Conference on the Network of the Future, 68-75, 2011 | 14 | 2011 |
Towards reinforcement learning for vulnerability analysis in power-economic systems T Wolgast, EMSP Veith, A Nieße Energy Informatics 4, 1-20, 2021 | 12 | 2021 |
Analyzing power grid, ICT, and market without domain knowledge using distributed artificial intelligence E Veith, S Balduin, N Wenninghoff, M Tröschel, L Fischer, A Nieße, ... arXiv preprint arXiv:2006.06074, 2020 | 12 | 2020 |
The adversarial resilience learning architecture for ai-based modelling, exploration, and operation of complex cyber-physical systems E Veith, N Wenninghoff, E Frost arXiv preprint arXiv:2005.13601, 2020 | 10 | 2020 |
Robust and deterministic scheduling of power grid actors E Frost, EMSP Veith, L Fischer 2020 7th International Conference on Control, Decision and Information …, 2020 | 9 | 2020 |
Pointing out the convolution problem of stochastic aggregation methods for the determination of flexibility potentials at vertical system interconnections J Gerster, M Sarstedt, E Veith, S Lehnhoff, L Hofmann arXiv preprint arXiv:2102.03430, 2021 | 7 | 2021 |
A lightweight distributed software agent for automatic demand—supply calculation in smart grids E Veith, B Steinbach, J Windeln International Journal On Advances in Internet Technology 7 (1), 97-113, 2014 | 7 | 2014 |
An architecture for reliable learning agents in power grids EMSP Veith ENERGY, 19, 2023 | 6 | 2023 |
An evolutionary training algorithm for artificial neural networks with dynamic offspring spread and implicit gradient information M Ruppert, EM Veith, B Steinbach Proceedings of the Sixth International Conference on Emerging Network …, 2014 | 6 | 2014 |
A lightweight messaging protocol for Smart Grids EM Veith, B Steinbach, J Windeln Proceedings of the Fifth International Conference on Emerging Network …, 2013 | 6 | 2013 |
Learning New Attack Vectors from Misuse Cases with Deep Reinforcement Learning E Veith, A Wellßow, M Uslar Frontiers in Energy Research 11, 157, 0 | 6 | |
Comparison of random sampling and heuristic optimization-based methods for determining the flexibility potential at vertical system interconnections J Gerster, S Lehnhoff, M Sarstedt, L Hofmann, EMSP Veith 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 1-6, 2021 | 5 | 2021 |