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ORCIDTimo P. Gros
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2020 – today
- 2024
[j3]Tristan Schneider
, Matheus V. A. Pedrosa, Timo P. Gros, Verena Wolf, Kathrin Flaßkamp:
Motion Primitives as the Action Space of Deep Q-Learning for Planning in Autonomous Driving. IEEE Trans. Intell. Transp. Syst. 25(11): 17852-17864 (2024)- [i2]Kevin Baum, Lisa Dargasz, Felix Jahn, Timo P. Gros, Verena Wolf:
Acting for the Right Reasons: Creating Reason-Sensitive Artificial Moral Agents. CoRR abs/2409.15014 (2024) - 2023
- [j2]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz:
Analyzing neural network behavior through deep statistical model checking. Int. J. Softw. Tools Technol. Transf. 25(3): 407-426 (2023) - [j1]Timo P. Gros, Joschka Groß, Daniel Höller, Jörg Hoffmann, Michaela Klauck, Hendrik Meerkamp, Nicola J. Müller, Lukas Schaller, Verena Wolf:
DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning - Extended Version. ACM Trans. Model. Comput. Simul. 33(4): 17:1-17:28 (2023) - [c12]Deborah Baum, Kevin Baum, Timo P. Gros, Verena Wolf:
XAI Requirements in Smart Production Processes: A Case Study. xAI (1) 2023: 3-24 - 2022
- [c11]Marcel Steinmetz, Daniel Fiser, Hasan Ferit Eniser, Patrick Ferber, Timo P. Gros, Philippe Heim, Daniel Höller, Xandra Schuler, Valentin Wüstholz, Maria Christakis, Jörg Hoffmann:
Debugging a Policy: Automatic Action-Policy Testing in AI Planning. ICAPS 2022: 353-361 - [c10]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Maximilian A. Köhl, Verena Wolf:
MoGym: Using Formal Models for Training and Verifying Decision-making Agents. CAV (2) 2022: 430-443 - [c9]Hasan Ferit Eniser, Timo P. Gros, Valentin Wüstholz, Jörg Hoffmann, Maria Christakis:
Metamorphic relations via relaxations: an approach to obtain oracles for action-policy testing. ISSTA 2022: 52-63 - [c8]David Groß, Michaela Klauck, Timo P. Gros, Marcel Steinmetz, Jörg Hoffmann, Stefan Gumhold:
Glyph-Based Visual Analysis of Q-Leaning Based Action Policy Ensembles on Racetrack. IV 2022: 1-10 - [d2]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Maximilian A. Köhl, Verena Wolf:
Artifact for the Tool Paper: MoGym: Using Formal Models for Training and Verifying Decision-making Agents. Zenodo, 2022
- 2021
- [c7]Timo P. Gros, Daniel Höller, Jörg Hoffmann, Michaela Klauck, Hendrik Meerkamp, Verena Wolf:
DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning. QEST 2021: 197-216 - [d1]Timo P. Gros, Holger Hermanns, Michaela Klauck, Maximilian A. Köhl:
Artifact of "MoGym: Using Formal Models for Training and Verifying Decision Agents". Zenodo, 2021 - 2020
- [c6]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz:
Deep Statistical Model Checking. FORTE 2020: 96-114 - [c5]Timo P. Gros, David Groß, Stefan Gumhold, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz:
TraceVis: Towards Visualization for Deep Statistical Model Checking. ISoLA (4) 2020: 27-46 - [c4]Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf:
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning. QEST 2020: 11-17 - [c3]Christel Baier, Maria Christakis, Timo P. Gros, David Groß, Stefan Gumhold, Holger Hermanns, Jörg Hoffmann, Michaela Klauck:
Lab Conditions for Research on Explainable Automated Decisions. TAILOR 2020: 83-90 - [c2]Timo P. Gros, Joschka Groß, Verena Wolf:
Real-Time Decision Making for a Car Manufacturing Process Using Deep Reinforcement Learning. WSC 2020: 3032-3044 - [i1]Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf:
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning - Extended Version. CoRR abs/2008.00766 (2020)
2010 – 2019
- 2019
- [c1]Timo P. Gros, Pascal Leo Held, Pascal Lauer, Niklas O. Metzger, Kallistos Weis:
aMAZEing Programming - Providing SKILLs to Fellow Students. SKILL 2019: 59-70
Coauthor Index
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