Timo P. Gros

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 15

Top Topics

Pspace Complete

Reinforcement Learning

Action Selection

Top Venues

Int. J. Softw. Tools Technol. Transf.

Publications

Deborah Baum, Kevin Baum, Timo P. Gros, Verena Wolf
XAI Requirements in Smart Production Processes: A Case Study. xAI (1) (2023)
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) (2023)
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) (2023)
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)
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)
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)
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)
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)
Timo P. Gros, Joschka Groß, Verena Wolf
Real-Time Decision Making for a Car Manufacturing Process Using Deep Reinforcement Learning. WSC (2020)
Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning - Extended Version. CoRR (2020)
Timo P. Gros, David Groß, Stefan Gumhold, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz
TraceVis: Towards Visualization for Deep Statistical Model Checking. ISoLA (4) (2020)
Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning. QEST (2020)
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)
Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz
Deep Statistical Model Checking. FORTE (2020)
Timo P. Gros, Pascal Leo Held, Pascal Lauer, Niklas O. Metzger, Kallistos Weis
aMAZEing Programming - Providing SKILLs to Fellow Students. SKILL (2019)