Daniel Palenicek

Quick Info

Research Interests

Reinforcement Learning, Machine Learning, Robotics

More Information

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Contact Information

Daniel Palenicek
TU Darmstadt, FG IAS,
Hochschulstr. 10, 64289 Darmstadt
Office. Room E304, Building S2|02
work+49-6151-16-25387

Daniel joined the Intelligent Autonomous System lab on October, 1st, 2021 as a PhD student. # (:titlesearch palenicek)

Before starting his PhD, Daniel completed his Bachelor's degree and Master's degree in Wirtschaftsinformatik at the Technische Universität Darmstadt. He wrote his Master's thesis entitled "Dyna-Style Model-Based Reinforcement Learning with Value Expansion" in the Computer Science Department under the supervision of Michael Lutter and Jan Peters.

Research Interests

Reinforcement Learning, Machine Learning, Robotics

Key References

  1. Belousov, B.; Abdulsamad H.; Klink, P.; Parisi, S.; Peters, J. (2021). Reinforcement Learning Algorithms: Analysis and Applications, Studies in Computational Intelligence, Springer International Publishing.   Download Article [PDF]   BibTeX Reference [BibTex]
  2. Zhou, M.; Luo, J.; Villella, J.; Yang, Y.; Rusu, D.; Miao, J.; Zhang, W.; Alban, M.; Fadakar, I.; Chen, Z.; Chongxi-Huang, A.; Wen, Y.; Hassanzadeh, K.; Graves, D.; Chen, D.; Zhu, Z.; Nguyen, N.; Elsayed, M.; Shao, K.; Ahilan, S.; Zhang, B.; Wu, J.; Fu, Z.; Rezaee, K.; Yadmellat, P.; Rohani, M.; Perez-Nieves, N.; Ni, Y.; Banijamali, S.; Cowen-Rivers, A.; Tian, Z.; Palenicek, D.; Bou-Ammar, H.; Zhang, H.; Liu, W.; Hao, J.; Wang, J. (2020). SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. Conference on Robot Learning (CoRL). Best System Paper Award. Download Article

  

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