| Deep statistical model checking TP Gros, H Hermanns, J Hoffmann, M Klauck, M Steinmetz Formal Techniques for Distributed Objects, Components, and Systems: 40th …, 2020 | 39 | 2020 |
| Tracking the Race Between Deep Reinforcement Learning and Imitation Learning TP Gros, D Höller, J Hoffmann, V Wolf International Conference on Quantitative Evaluation of Systems, 11-17, 2020 | 15 | 2020 |
| Real-Time Decision Making for a Car Manufacturing Process Using Deep Reinforcement Learning TP Gros, J Groß, V Wolf 2020 Winter Simulation Conference (WSC), 3032-3044, 2020 | 12 | 2020 |
| TraceVis: towards visualization for deep statistical model checking TP Gros, D Groß, S Gumhold, J Hoffmann, M Klauck, M Steinmetz Leveraging Applications of Formal Methods, Verification and Validation …, 2021 | 11 | 2021 |
| Lab Conditions for Research on Explainable Automated Decisions C Baier, M Christakis, TP Gros, D Groß, S Gumhold, H Hermanns, ... Trustworthy AI–Integrating Learning, Optimization and Reasoning: First …, 2021 | 10 | 2021 |
| Metamorphic relations via relaxations: An approach to obtain oracles for action-policy testing HF Eniser, TP Gros, V Wüstholz, J Hoffmann, M Christakis Proceedings of the 31st ACM SIGSOFT International Symposium on Software …, 2022 | 9 | 2022 |
| DSMC evaluation stages: Fostering robust and safe behavior in deep reinforcement learning TP Gros, D Höller, J Hoffmann, M Klauck, H Meerkamp, V Wolf Quantitative Evaluation of Systems: 18th International Conference, QEST 2021 …, 2021 | 9 | 2021 |
| Debugging a Policy: Automatic Action-Policy Testing in AI Planning M Steinmetz, D Fišer, HF Eniser, P Ferber, TP Gros, P Heim, D Höller, ... Proceedings of the International Conference on Automated Planning and …, 2022 | 8 | 2022 |
| MoGym: Using Formal Models for Training and Verifying Decision-making Agents TP Gros, H Hermanns, J Hoffmann, M Klauck, MA Köhl, V Wolf International Conference on Computer Aided Verification, 430-443, 2022 | 7 | 2022 |
| Analyzing neural network behavior through deep statistical model checking TP Gros, H Hermanns, J Hoffmann, M Klauck, M Steinmetz International Journal on Software Tools for Technology Transfer 25 (3), 407-426, 2023 | 6 | 2023 |
| Tracking the Race Between Deep Reinforcement Learning and Imitation Learning - Extended Version TP Gros, D Höller, J Hoffmann, V Wolf arXiv preprint arXiv:2008.00766, 2020 | 5 | 2020 |
| Models and Infrastructure used in “Deep Statistical Model Checking”(2020) TP Gros, H Hermanns, J Hoffmann, M Klauck, M Steinmetz Available at DOI: https://doi. org/10.5281/zenodo 3760098, 0 | 5 | |
| XAI Requirements in Smart Production Processes: A Case Study D Baum, K Baum, TP Gros, V Wolf World Conference on Explainable Artificial Intelligence, 3-24, 2023 | 4 | 2023 |
| Tracking the race: Analyzing racetrack agents trained with imitation learning and deep reinforcement learning TP Gros Master's thesis, 2021 | 4 | 2021 |
| DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning–Extended Version TP Gros, J Groß, D Höller, J Hoffmann, M Klauck, H Meerkamp, NJ Müller, ... ACM Transactions on Modeling and Computer Simulation 33 (4), 1-28, 2023 | 3 | 2023 |
| Markov automata taken by Storm TP Gros Bachelor's thesis, Saarland University, Germany, 2018 | 3 | 2018 |
| Glyph-Based Visual Analysis of Q-Learning Based Action Policy Ensembles on Racetrack D Groß, M Klauck, TP Gros, M Steinmetz, J Hoffmann, S Gumhold International Conference on Information Visualisation (IV’22), 2022 | 2 | 2022 |
| Debugging a Policy: A Framework for Automatic Action Policy Testing M Steinmetz, TP Gros, P Heim, D Höller, J Hoffmann PRL@ ICAPS, 2021 | 1 | 2021 |
| Safe Reinforcement Learning Through Regret and State Restorations in Evaluation Stages TP Gros, NJ Müller, D Höller, V Wolf | | 2024 |
| Comparing State-of-the-art Graph Neural Networks and Transformers for General Policy Learning NJ Müller, P Sánchez, J Hoffmann, V Wolf, TP Gros | | 2024 |
Joerg HoffmannProfessor, Saarland Informatics Campus, Saarland University and German Research Center for AI (DFKI)在 cs.uni-saarland.de 的电子邮件经过验证
