- Using Simulation Optimization to Improve Zero-shot Policy Transfer of Quadrotors. ArXiv abs/2201.01369, 2022 more… BibTeX
- Multi-agent deep reinforcement learning: a survey. Artificial Intelligence Review, 2021 more… BibTeX Full text ( DOI )
- The Successful Ingredients of Policy Gradient Algorithms. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, 2021 more… BibTeX Full text ( DOI )
Sven Gronauer, M.Sc.
Technical Universtiy Munich
Chair of Data Processing
Arcisstr. 21
80333 Munich, Germany
Phone: +49 (0)89 289 23631
Fax: +49 (0)89 289 23600
E-Mail: sven.gronauer@tum.de
Room: Z932
Research Interests
- Reinforcement Learning with focus on real-world systems:
- Transfer of control polices from simulation to real world (sim-to-real)
- Safe exploraration and generation of data
- Robustness of learned control strategies
- Learning with mulitple agents (Multi-agent Reinforcement Learning)