Journal Papers
Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, L.; Kroemer, O.; Peters, J. (accepted). Probabilistic Movement Primitives for Coordination of Multiple Human-Robot Collaborative Tasks, Autonomous Robots (AURO).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Maeda, G.; Ewerton, M.; Neumann, G.; Lioutikov, R.; Peters, J. (accepted). Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot Collaboration, International Journal of Robotics Research (IJRR).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J. (accepted). Learning Movement Primitive Libraries through Probabilistic Segmentation, International Journal of Robotics Research (IJRR).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Wirth, C. and Akrour, R. and Fürnkranz, J. and Neumann G. (accepted). A Survey of Preference-Based Reinforcement Learning Methods, Journal of Machine Learning Research (JMLR).   See Details [Details]   BibTeX Reference [BibTex]

Osa, T.; Ghalamzan, E. A. M.; Stolkin, R.; Lioutikov, R.; Peters, J.; Neumann, G. (2017). Guiding Trajectory Optimization by Demonstrated Distributions, IEEE Robotics and Automation Letters (RA-L), 2, 2, pp.819-826, IEEE.   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]

Abdolmaleki, A.; Lau, N.; Reis, L.; Peters, J.; Neumann, G. (2016). Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller, Journal of Intelligent & Robotic Systems.   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 (ML), 104, 2-3, pp.337-357.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Kupcsik, A.G.; Deisenroth, M.P.; Peters, J.; Ai Poh, L.; Vadakkepat, V.; Neumann, G. (2015). Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills, Artificial Intelligence.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Lioutikov, R.; Paraschos, A.; Peters, J.; Neumann, G. (2014). Generalizing Movements with Information Theoretic Stochastic Optimal Control, Journal of Aerospace Information Systems, 11, 9, pp.579-595.   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]

Dann, C.; Neumann, G.; Peters, J. (2014). Policy Evaluation with Temporal Differences: A Survey and Comparison, Journal of Machine Learning Research, 15, March, pp.809-883.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Rueckert, E.A.; Neumann, G.; Toussaint, M.; Maass, W. (2013). Learned graphical models for probabilistic planning provide a new class of movement primitives, Frontiers in Computational Neuroscience, 6, 97.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Deisenroth, M. P.; Neumann, G.; Peters, J. (2013). A Survey on Policy Search for Robotics, Foundations and Trends in Robotics, 21, pp.388-403.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Rueckert, E.A.; Neumann, G. (2012). Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation, Artificial Life.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Hauser, H.; Neumann, G.; Ijspeert A.; Maass W. (2011). Biologically Inspired Kinematic Synergies enable Linear Balance Control of a Humanoid Robot, Biological Cybernetics.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]
 
Conference and Workshop Papers
Tangkaratt, V.; van Hoof, H.; Parisi, S.; Neumann, G.; Peters, J.; Sugiyama, M. (2017). Policy Search with High-Dimensional Context Variables, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Gebhardt, G. H. W.; Kupcsik, A.; Neumann, G. (2017). The Kernel Kalman Rule - Efficient Nonparametric Inference with Recursive Least Squares, Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Farraj, F. B.; Osa, T.; Pedemonte, N.; Peters, J.; Neumann, G.; Giordano, P.R. (2017). A Learning-based Shared Control Architecture for Interactive Task Execution, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

End, F.; Akrour, R.; Peters, J.; Neumann, G. (2017). Layered Direct Policy Search for Learning Hierarchical Skills, Proceedings of the International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Gabriel, A.; Akrour, R.; Peters, J.; Neumann, G. (2017). Empowered Skills, Proceedings of the International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Abdulsamad, H.; Arenz, O.; Peters, J.; Neumann, G. (2017). State-Regularized Policy Search for Linearized Dynamical Systems, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Abdolmaleki A. and Price, B. and Neumann, G. (2017). Deriving and Improving CMA-ES with Information Geometric Trust Regions, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Abdolmaleki A. and Price, B. and Lau, N and P. Reis and Neumann, G. (2017). Contextual CMA-ES, International Joint Conference on Artificial Intelligence (IJCAI) .   See Details [Details]   BibTeX Reference [BibTex]

Osa, T.; Peters, J.; Neumann, G. (2016). Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies, Proceedings of the International Symposium on Experimental Robotics (ISER).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O.; Abdulsamad, H.; Neumann, G. (2016). Optimal Control and Inverse Optimal Control by Distribution Matching, Proceedings of the International Conference on Intelligent Robots and Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Modugno, V.; Neumann, G.; Rueckert, E.; Oriolo, G.; Peters, J.; Ivaldi, S. (2016). Learning soft task priorities for control of redundant robots, Proceedings of the International Conference on Robotics and Automation (ICRA).   See Details [Details]   BibTeX Reference [BibTex]

Ewerton, M.; Maeda, G.; Neumann, G.; Kisner, V.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2016). Movement Primitives with Multiple Phase Parameters, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.201--206.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Akrour, R.; Abdolmaleki, A.; Abdulsamad, H.; Neumann, G. (2016). Model-Free Trajectory Optimization for Reinforcement Learning, Proceedings of the International Conference on Machine Learning (ICML).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Belousov, B.; Neumann, G.; Rothkopf, C.; Peters, J. (2016). Catching heuristics are optimal control policies, Advances in Neural Information Processing Systems (NIPS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Koert, D.; Maeda, G.J.; Lioutikov, R.; Neumann, G.; Peters, J. (2016). Demonstration Based Trajectory Optimization for Generalizable Robot Motions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Gomez-Gonzalez, S.; Neumann, G.; Schoelkopf, B.; Peters, J. (2016). Using Probabilistic Movement Primitives for Striking Movements, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   BibTeX Reference [BibTex]

Abdolmaleki, A; Lau, N.; Reis, L.; Neumann, G.; (2016). Non-Parametric Contextual Stochastic Search, Proceedings of the International Conference on Intelligent Robots and Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

van Hoof, H.; Peters, J.; Neumann, G. (2015). Learning of Non-Parametric Control Policies with High-Dimensional State Features, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).   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]

Rueckert, E.; Mundo, J.; Paraschos, A.; Peters, J.; Neumann, G. (2015). Extracting Low-Dimensional Control Variables for Movement Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Ewerton, M.; Neumann, G.; Lioutikov, R.; Ben Amor, H.; Peters, J.; Maeda, G. (2015). Learning Multiple Collaborative Tasks with a Mixture of Interaction Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.1535--1542.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Lioutikov, R.; Neumann, G.; Maeda, G.J.; Peters, J. (2015). Probabilistic Segmentation Applied to an Assembly Task, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Paraschos, A.; Rueckert, E.; Peters, J; Neumann, G. (2015). Model-Free Probabilistic Movement Primitives for Physical Interaction, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Ewerton, M.; Neumann, G.; Lioutikov, R.; Ben Amor, H.; Peters, J.; Maeda, G. (2015). Modeling Spatio-Temporal Variability in Human-Robot Interaction with Probabilistic Movement Primitives, Workshop on Machine Learning for Social Robotics, ICRA.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Ewerton, M.; Maeda, G.J.; Peters, J.; Neumann, G. (2015). Learning Motor Skills from Partially Observed Movements Executed at Different Speeds, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp.456--463.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Peters, J. (2015). A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives with Phase Estimation, Proceedings of the International Symposium of Robotics Research (ISRR).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Koc, O.; Maeda, G.; Neumann, G.; Peters, J. (2015). Optimizing Robot Striking Movement Primitives with Iterative Learning Control, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   BibTeX Reference [BibTex]

van Hoof, H.; Hermans, T.; Neumann, G.; Peters, J. (2015). Learning Robot In-Hand Manipulation with Tactile Features, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Abdolmaleki, A. and Lau, N. and Reis, L. and Neumann, G. (2015). Regularized Covariance Estimation for Weighted Maximum Likelihood Policy Search Methods, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Abdolmaleki, A.; Lioutikov, R.; Peters, J; Lau, N.; Reis, L.; Neumann, G. (2015). Model-Based Relative Entropy Stochastic Search, Advances in Neural Information Processing Systems (NIPS), MIT Press.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Dann, C.; Neumann, G.; Peters, J. (2015). Policy Evaluation with Temporal Differences: A Survey and Comparison, Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling (ICAPS), pp.359-360.   See Details [Details]   BibTeX Reference [BibTex]

Wirth, C.; Fürnkranz, J.; Neumann G. (2015). Model-Free Preference-Based Reinforcement Learning, Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Gebhardt, G. H. W.; Kupcsik, A.; Neumann, G. (2015). Learning Subspace Conditional Embedding Operators, Large-Scale Kernel Learning Workshop at ICML 2015.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Kroemer, O.; van Hoof, H.; Neumann, G.; Peters, J. (2014). Learning to Predict Phases of Manipulation Tasks as Hidden States, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Ben Amor, H.; Neumann, G.; Kamthe, S.; Kroemer, O.; Peters, J. (2014). Interaction Primitives for Human-Robot Cooperation Tasks , Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Luck, K.S.; Neumann, G.; Berger, E.; Peters, J.; Ben Amor, H. (2014). Latent Space Policy Search for Robotics, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Gomez, V.; Kappen, B; Peters, J.; Neumann, G (2014). Policy Search for Path Integral Control, Proceedings of the European Conference on Machine Learning (ECML).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Maeda, G.J.; Ewerton, M.; Lioutikov, R.; Amor, H.B.; Peters, J.; Neumann, G. (2014). Learning Interaction for Collaborative Tasks with Probabilistic Movement Primitives, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp.527--534.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Colome, A.; Neumann, G.; Peters, J.; Torras, C. (2014). Dimensionality Reduction for Probabilistic Movement Primitives, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Rueckert, E.; Mindt, M.; Peters, J.; Neumann, G. (2014). Robust Policy Updates for Stochastic Optimal Control, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   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]

Peters, J.; Kober, J.; Muelling, K.; Kroemer, O.; Neumann, G. (2013). Towards Robot Skill Learning: From Simple Skills to Table Tennis, Proceedings of the European Conference on Machine Learning (ECML), Nectar Track.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Kupcsik, A.G.; Deisenroth, M.P.; Peters, J.; Neumann, G. (2013). Data-Efficient Generalization of Robot Skills with Contextual Policy Search, Proceedings of the National Conference on Artificial Intelligence (AAAI) .   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]

Neumann, G.; Kupcsik, A.G.; Deisenroth, M.P.; Peters, J. (2013). Information-Theoretic Motor Skill Learning, Proceedings of the AAAI 2013 Workshop on Intelligent Robotic Systems.   See Details [Details]   BibTeX Reference [BibTex]

Paraschos, A.; Neumann, G; Peters, J. (2013). A Probabilistic Approach to Robot Trajectory Generation, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   Download Article [PDF]   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]

Ben Amor, H.; Kroemer, O.; Hillenbrand, U.; Neumann, G.; Peters, J. (2012). Generalization of Human Grasping for Multi-Fingered Robot Hands, Proceedings of the International Conference on Robot Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Neumann, G. (2011). Variational Inference for Policy Search in Changing Situations, Proceedings of the International Conference on Machine Learning (ICML 2011) .   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Rueckert, E.A.; Neumann, G. (2011). A study of Morphological Computation by using Probabilistic Inference for Motor Planning, Proceedings of the 2nd International Conference on Morphological Computation (ICMC), pp.51--53.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Neumann, G.; Peters, J. (2009). Fitted Q-iteration by Advantage Weighted Regression, Advances in Neural Information Processing Systems 22 (NIPS 2008), Cambridge, MA: MIT Press.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Neumann, G.; Maass, W; Peters, J. (2009). Learning Complex Motions by Sequencing Simpler Motion Templates, Proceedings of the International Conference on Machine Learning (ICML2009).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Hauser, H.; Neumann, G.; Ijspeert, A.; Maass, W.; (2007). Biologically Inspired Kinematic Synergies Provide a New Paradigm for Balance Control of Humanoid Robots, Proceedings of the 7th IEEE RAS/RSJ Conference on Humanoids Robots (HUMANOIDS07).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Neumann, G.; Pfeiffer, M.; Maass, W. (2007). Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs, European Conference on Machine Learning (ECML) 2007.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

  

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