Timo P. Gros

According to our database, Timo P. Gros authored at least 15 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning - Extended Version.

Timo P. Gros, Joschka Groß, Daniel Höller, Jörg Hoffmann, Michaela Klauck, Hendrik Meerkamp, Nicola J. Müller, Lukas Schaller, Verena Wolf

ACM Trans. Model. Comput. Simul., October, 2023

Analyzing neural network behavior through deep statistical model checking.

Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz

Int. J. Softw. Tools Technol. Transf., June, 2023

XAI Requirements in Smart Production Processes: A Case Study.

Deborah Baum, Kevin Baum, Timo P. Gros, Verena Wolf

Proceedings of the Explainable Artificial Intelligence, 2023

2022

Glyph-Based Visual Analysis of Q-Leaning Based Action Policy Ensembles on Racetrack.

David Groß, Michaela Klauck, Timo P. Gros, Marcel Steinmetz, Jörg Hoffmann, Stefan Gumhold

Proceedings of the 26th International Conference Information Visualisation, 2022

Metamorphic relations via relaxations: an approach to obtain oracles for action-policy testing.

Hasan Ferit Eniser, Timo P. Gros, Valentin Wüstholz, Jörg Hoffmann, Maria Christakis

Proceedings of the ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, South Korea, July 18, 2022

MoGym: Using Formal Models for Training and Verifying Decision-making Agents.

Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Maximilian A. Köhl, Verena Wolf

Proceedings of the Computer Aided Verification - 34th International Conference, 2022

Debugging a Policy: Automatic Action-Policy Testing in AI Planning.

Marcel Steinmetz, Daniel Fiser, Hasan Ferit Eniser, Patrick Ferber, Timo P. Gros, Philippe Heim, Daniel Höller, Xandra Schuler, Valentin Wüstholz, Maria Christakis, Jörg Hoffmann

Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

2021

DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning.

Timo P. Gros, Daniel Höller, Jörg Hoffmann, Michaela Klauck, Hendrik Meerkamp, Verena Wolf

Proceedings of the Quantitative Evaluation of Systems - 18th International Conference, 2021

2020

Tracking the Race Between Deep Reinforcement Learning and Imitation Learning - Extended Version.

Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf

CoRR, 2020

Real-Time Decision Making for a Car Manufacturing Process Using Deep Reinforcement Learning.

Timo P. Gros, Joschka Groß, Verena Wolf

Proceedings of the Winter Simulation Conference, 2020

Lab Conditions for Research on Explainable Automated Decisions.

Christel Baier, Maria Christakis, Timo P. Gros, David Groß, Stefan Gumhold, Holger Hermanns, Jörg Hoffmann, Michaela Klauck

Proceedings of the Trustworthy AI - Integrating Learning, Optimization and Reasoning, 2020

Tracking the Race Between Deep Reinforcement Learning and Imitation Learning.

Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf

Proceedings of the Quantitative Evaluation of Systems - 17th International Conference, 2020

TraceVis: Towards Visualization for Deep Statistical Model Checking.

Timo P. Gros, David Groß, Stefan Gumhold, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz

Proceedings of the Leveraging Applications of Formal Methods, Verification and Validation: Tools and Trends, 2020

Deep Statistical Model Checking.

Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz

Proceedings of the Formal Techniques for Distributed Objects, Components, and Systems, 2020

2019

aMAZEing Programming - Providing SKILLs to Fellow Students.

Timo P. Gros, Pascal Leo Held, Pascal Lauer, Niklas O. Metzger, Kallistos Weis

Proceedings of the Studierendenkonferenz Informatik, 2019