Books

Daniel, C. and Neumann, G.; Hierarchical Relative Entropy Policy Search; Akademikerverlag; ISBN 978-3-639-47599-9

Journal Papers
Paraschos, A.; Daniel, C.; Peters, J.; Neumann, G. (2018). Using Probabilistic Movement Primitives in Robotics, Autonomous Robots (AURO), 42, 3, pp.529-551.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; Neumann, G.; Kroemer, O.; Peters, J. (2016). Hierarchical Relative Entropy Policy Search, Journal of Machine Learning Research (JMLR), 17, pp.1-50.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; van Hoof, H.; Peters, J.; Neumann, G. (2016). Probabilistic Inference for Determining Options in Reinforcement Learning, Machine Learning (MLJ), 104, 2-3, pp.337-357.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; Kroemer, O.; Viering, M.; Metz, J.; Peters, J. (2015). Active Reward Learning with a Novel Acquisition Function, Autonomous Robots (AURO), 39, pp.389-405.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Neumann, G.; Daniel, C.; Paraschos, A.; Kupcsik, A.; Peters, J. (2014). Learning Modular Policies for Robotics, Frontiers in Computational Neuroscience.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]
Conference and Workshop Papers
Daniel, C.; Taylor, J.; Nowozin, S. (2016). Learning Step Size Controllers for Robust Neural Network Training, National Conference of the American Association for Artificial Intelligence (AAAI).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Kroemer, O.; Daniel, C.; Neumann, G; van Hoof, H.; Peters, J. (2015). Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks, Proceedings of the International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Parisi, S.; Abdulsamad, H.; Paraschos, A.; Daniel, C.; Peters, J. (2015). Reinforcement Learning vs Human Programming in Tetherball Robot Games, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; Viering, M.; Metz, J.; Kroemer, O.; Peters, J. (2014). Active Reward Learning, Proceedings of Robotics: Science & Systems (R:SS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; Neumann, G.; Kroemer, O.; Peters, J. (2013). Learning Sequential Motor Tasks, Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; Neumann, G.; Peters, J. (2013). Autonomous Reinforcement Learning with Hierarchical REPS, Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN) .   See Details [Details]   BibTeX Reference [BibTex]

Paraschos, A.; Daniel, C.; Peters, J.; Neumann, G (2013). Probabilistic Movement Primitives, Advances in Neural Information Processing Systems (NIPS), MIT Press.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; Neumann, G.; Peters, J. (2012). Hierarchical Relative Entropy Policy Search, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2012).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Daniel, C.; Neumann, G.; Peters, J. (2012). Learning Concurrent Motor Skills in Versatile Solution Spaces, Proceedings of the International Conference on Robot Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

  

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