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Number of items: 74.

Hüttenrauch, M. and Šošić, A. and Neumann, G. (2019):
Deep Reinforcement Learning for Swarm Systems.
In: Journal of Machine Learning Research, pp. 1-31, 20, (54), [Online-Edition: http://jmlr.csail.mit.edu/papers/volume20/18-476/18-476.pdf],
[Article]

Osa, T. and Peters, J. and Neumann, G. (2018):
Hierarchical Reinforcement Learning of Multiple Grasping Strategies with Human Instructions.
In: Advanced Robotics, pp. 955-968, 32, (18), DOI: 10.1080/01691864.2018.1509018,
[Article]

Osa, T. and Pajarinen, J. and Neumann, G. and Bagnell, J.A. and Abbeel, P. and Peters, J. (2018):
An Algorithmic Perspective on Imitation Learning.
In: Foundations and Trends in Robotics, pp. 1-179, 7, (1-2), ISSN 1935-8253, 1935-8261 (elektronisch),
[Online-Edition: https://www.nowpublishers.com/article/DownloadSummary/ROB-05...],
[Article]

Koert, D. and Maeda, G. and Neumann, G. and Peters, J. (2018):
Learning Coupled Forward-Inverse Models with Combined Prediction Errors.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/DorotheaKoert/c...],
[Conference or Workshop Item]

Gebhardt, G.H.W. and Daun, K. and Schnaubelt, M. and Neumann, G. (2018):
Learning Robust Policies for Object Manipulation with Robot Swarms.
In: Proceedings of the IEEE International Conference on Robotics and Automation, In: 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, May 21-25, 2018, [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/GregorGebhardt/...],
[Conference or Workshop Item]

Hüttenrauch, M. and Šošić, A. and Neumann, G. (2018):
Local Communication Protocols for Learning Complex Swarm Behaviors With Deep Reinforcement Learning.
In: International Conference on Swarm Intelligence, [Conference or Workshop Item]

Paraschos, A. and Rueckert, E. and Peters, J. and Neumann, G. (2018):
Probabilistic Movement Primitives under Unknown System Dynamics.
In: Advanced Robotics, pp. 297-310, 32, (6), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Alumni/AlexandrosPar...],
[Article]

Paraschos, A. and Daniel, C. and Peters, J. and Neumann, G. (2018):
Using Probabilistic Movement Primitives in Robotics.
In: Autonomous Robots, pp. 529-551, 42, (3), ISSN 0929-5593,
[Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/AlexandrosParas...],
[Article]

Belousov, B. and Neumann, G. and Rothkopf, C. A. and Peters, J. (2017):
Catching heuristics are optimal control policies.
In: Proceedings of the Karniel Thirteenth Computational Motor Control Workshop, [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Gabriel, A. and Akrour, R. and Peters, J. and Neumann, G. (2017):
Empowered Skills.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Research/Overview/ic...],
[Conference or Workshop Item]

Hüttenrauch, M. and Šošić, A. and Neumann, G. (2017):
Guided Deep Reinforcement Learning for Swarm Systems.
In: AAMAS Workshop on Autonomous Robots and Multirobot Systems, [Online-Edition: https://arxiv.org/abs/1709.06011],
[Conference or Workshop Item]

Osa, T. and Ghalamzan, E. A. M. and Stolkin, R. and Lioutikov, R. and Peters, J. and Neumann, G. (2017):
Guiding Trajectory Optimization by Demonstrated Distributions.
In: IEEE Robotics and Automation Letters, ieee, pp. 819-826, (2), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Article]

Pajarinen, J. and Kyrki, V. and Koval, M. and Srinivasa, S. and Peters, J. and Neumann, G. (2017):
Hybrid Control Trajectory Optimization under Uncertainty.
In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Gebhardt, G. H. W. and Kupcsik, A. G. and Neumann, G. (2017):
The Kernel Kalman Rule - Efficient Nonparametric Inference with Recursive Least Squares.
In: Proceedings of the National Conference on Artificial Intelligence (AAAI), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/GregorGebhardt/...],
[Conference or Workshop Item]

End, F. and Akrour, R. and Peters, J. and Neumann, G. (2017):
Layered Direct Policy Search for Learning Hierarchical Skills.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Research/Overview/ic...],
[Conference or Workshop Item]

Gebhardt, G.H.W. and Daun, K. and Schnaubelt, M. and Hendrich, A. and Kauth, D. and Neumann, G. (2017):
Learning to Assemble Objects with a Robot Swarm.
international foundation for autonomous agents and multiagent systems, In: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS 17), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/GregorGebhardt/...],
[Conference or Workshop Item]

Farraj, F. B. and Osa, T. and Pedemonte, N. and Peters, J. and Neumann, G. and Giordano, P.R. (2017):
A Learning-based Shared Control Architecture for Interactive Task Execution.
In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Akrour, R. and Sorokin, D. and Peters, J. and Neumann, G. (2017):
Local Bayesian Optimization of Motor Skills.
In: Proceedings of the International Conference on Machine Learning (ICML), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Kupcsik, A. G. and Deisenroth, M. P. and Peters, J. and Ai Poh, L. and Vadakkepat, V. and Neumann, G. (2017):
Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills.
In: Artificial Intelligence, pp. 415-439, 247, ISSN 0004-3702,
[Online-Edition: http://www.ias.informatik.tu-darmstadt.de/uploads/Publicatio...],
[Article]

van Hoof, H. and Neumann, G. and Peters, J. (2017):
Non-parametric Policy Search with Limited Information Loss.
In: Journal of Machine Learning Research, pp. 1-46, (73), ISSN 0885-6125,
[Online-Edition: https://dl.acm.org/citation.cfm?id=3176817],
[Article]

Maeda, G. and Ewerton, M. and Neumann, G. and Lioutikov, R. and Peters, J. (2017):
Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot Collaboration.
In: International Journal of Robotics Research, pp. 1579-1594, 36, (13-14), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/PubGJMaeda/phas...],
[Article]

Tangkaratt, V. and van Hoof, H. and Parisi, S. and Neumann, G. and Peters, J. and Sugiyama, M. (2017):
Policy Search with High-Dimensional Context Variables.
In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Maeda, G. and Neumann, G. and Ewerton, M. and Lioutikov, R. and Kroemer, O. and Peters, J. (2017):
Probabilistic Movement Primitives for Coordination of Multiple Human-Robot Collaborative Tasks.
In: Autonomous Robots, pp. 593-612, 41, (3), ISSN 0929-5593,
[Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/PubGJMaeda/gjm_...],
[Article]

Abdulsamad, H. and Arenz, O. and Peters, J. and Neumann, G. (2017):
State-Regularized Policy Search for Linearized Dynamical Systems.
In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Belousov, B. and Neumann, G. and Rothkopf, C. and Peters, J. (2016):
Catching heuristics are optimal control policies.
In: Advances in Neural Information Processing Systems (NIPS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Abdolmaleki, A. and Lau, N. and Reis, L. and Peters, J. and Neumann, G. (2016):
Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller.
In: Journal of Intelligent & Robotic Systems, pp. 393-408, 83, (3-4), [Online-Edition: https://link.springer.com/article/10.1007/s10846-016-0347-y],
[Article]

Koert, D. and Maeda, G. J. and Lioutikov, R. and Neumann, G. and Peters, J. (2016):
Demonstration Based Trajectory Optimization for Generalizable Robot Motions.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/DorotheaKoert/D...],
[Conference or Workshop Item]

Osa, T. and Peters, J. and Neumann, G. (2016):
Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies.
In: Proceedings of the International Symposium on Experimental Robotics (ISER), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Hüttenrauch, M. and Šošić, A. and Neumann, G. (2016):
Guided Deep Reinforcement Learning for Swarm Systems.
In: NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, [Conference or Workshop Item]

Modugno, V. and Neumann, G. and Rueckert, E. and Oriolo, G. and Peters, J. and Ivaldi, S. (2016):
Learning soft task priorities for control of redundant robots.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Conference or Workshop Item]

Akrour, R. and Abdolmaleki, A. and Abdulsamad, H. and Neumann, G. (2016):
Model-Free Trajectory Optimization for Reinforcement Learning.
In: Proceedings of the International Conference on Machine Learning (ICML), [Online-Edition: http://proceedings.mlr.press/v48/akrour16.pdf],
[Conference or Workshop Item]

Ewerton, M. and Maeda, G. and Neumann, G. and Kisner, V. and Kollegger, G. and Wiemeyer, J. and Peters, J. (2016):
Movement Primitives with Multiple Phase Parameters.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/MarcoEwerton/ew...],
[Conference or Workshop Item]

Arenz, O. and Abdulsamad, H. and Neumann, G. (2016):
Optimal Control and Inverse Optimal Control by Distribution Matching.
In: Proceedings of the International Conference on Intelligent Robots and Systems (IROS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/OlegArenz/OC an...],
[Conference or Workshop Item]

Gomez-Gonzalez, S. and Neumann, G. and Schoelkopf, B. and Peters, J. (2016):
Using Probabilistic Movement Primitives for Striking Movements.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), [Conference or Workshop Item]

Rueckert, E. and Mundo, J. and Paraschos, A. and Peters, J. and Neumann, G. (2015):
Extracting Low-Dimensional Control Variables for Movement Primitives.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Conference or Workshop Item]

Ewerton, M. and Maeda, G. J. and Peters, J. and Neumann, G. (2015):
Learning Motor Skills from Partially Observed Movements Executed at Different Speeds.
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), [Online-Edition: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=735...],
[Conference or Workshop Item]

Ewerton, M. and Neumann, G. and Lioutikov, R. and Ben Amor, H. and Peters, J. and Maeda, G. (2015):
Learning Multiple Collaborative Tasks with a Mixture of Interaction Primitives.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Conference or Workshop Item]

van Hoof, H. and Hermans, T. and Neumann, G. and Peters, J. (2015):
Learning Robot In-Hand Manipulation with Tactile Features.
In: International Conference on Humanoid Robots (HUMANOIDS), Seoul, 3.-5.11.2015, [Online-Edition: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=736...],
[Conference or Workshop Item]

van Hoof, H. and Peters, J. and Neumann, G. (2015):
Learning of Non-Parametric Control Policies with High-Dimensional State Features.
In: Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Abdolmaleki, A. and Lioutikov, R. and Peters, J and Lau, N. and Reis, L. and Neumann, G. (2015):
Model-Based Relative Entropy Stochastic Search.
mit press, In: Advances in Neural Information Processing Systems (NIPS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/GerhardNeumann/...],
[Conference or Workshop Item]

Paraschos, A. and Rueckert, E. and Peters, J and Neumann, G. (2015):
Model-Free Probabilistic Movement Primitives for Physical Interaction.
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/PubAlexParascho...],
[Conference or Workshop Item]

Ewerton, M. and Neumann, G. and Lioutikov, R. and Ben Amor, H. and Peters, J. and Maeda, G. (2015):
Modeling Spatio-Temporal Variability in Human-Robot Interaction with Probabilistic Movement Primitives.
[Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/MarcoEwerton/ew...],
[Other]

Koc, O. and Maeda, G. and Neumann, G. and Peters, J. (2015):
Optimizing Robot Striking Movement Primitives with Iterative Learning Control.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), In: 5th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2015, Seoul, 3.-5.11.2015, [Online-Edition: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=736...],
[Conference or Workshop Item]

Dann, C. and Neumann, G. and Peters, J. (2015):
Policy Evaluation with Temporal Differences: A Survey and Comparison.
In: Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling (ICAPS), [Conference or Workshop Item]

Maeda, G. and Neumann, G. and Ewerton, M. and Lioutikov, R. and Peters, J. (2015):
A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives with Phase Estimation.
In: Proceedings of the International Symposium of Robotics Research (ISRR), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Team/PubGJMaeda/ISRR...],
[Conference or Workshop Item]

Lioutikov, R. and Neumann, G. and Maeda, G. J. and Peters, J. (2015):
Probabilistic Segmentation Applied to an Assembly Task.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Conference or Workshop Item]

Kroemer, O. and Daniel, C. and Neumann, G. and van Hoof, H. and Peters, J. (2015):
Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks.
In: Proceedings of the International Conference on Robotics and Automation (ICRA), In: Proceedings of the International Conference on Robotics and Automation (ICRA), [Online-Edition: http://],
[Conference or Workshop Item]

Neumann, G. and Daniel, C. and Paraschos, A. and Kupcsik, A. and Peters, J. (2014):
Learning Modular Policies for Robotics.
In: Frontiers in Computational Neuroscience, DOI: 10.3389/fncom.2014.00062,
[Online-Edition: http://www.frontiersin.org/Journal/Abstract.aspx?s=237&name=...],
[Article]

Colome, A. and Neumann, G. and Peters, J. and Torras, C. (2014):
Dimensionality Reduction for Probabilistic Movement Primitives.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), Madrid, November 18-20th, 2014, [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Publications/Colome_H...],
[Conference or Workshop Item]

Lioutikov, R. and Paraschos, A. and Peters, J. and Neumann, G. (2014):
Generalizing Movements with Information Theoretic Stochastic Optimal Control.
In: Journal of Aerospace Information Systems, pp. 579-595, 11, (9), [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Site/EditPublication/...],
[Article]

Ben Amor, H. and Neumann, G. and Kamthe, S. and Kroemer, O. and Peters, J. (2014):
Interaction Primitives for Human-Robot Cooperation Tasks.
In: Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA), [Online-Edition: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=690...],
[Conference or Workshop Item]

Luck, K. S. and Neumann, G. and Berger, E. and Peters, J. and Ben Amor, H. (2014):
Latent Space Policy Search for Robotics.
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), Chicago, IL, 14-18 September 2014, [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Publications/Luck_IRO...],
[Conference or Workshop Item]

Maeda, G. J. and Ewerton, M. and Lioutikov, R. and Amor, H. B. and Peters, J. and Neumann, G. (2014):
Learning Interaction for Collaborative Tasks with Probabilistic Movement Primitives.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), Madrid, November 18-20th, 2014, [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Team/PubGJMaeda/maeda...],
[Conference or Workshop Item]

Kroemer, O. and van Hoof, H. and Neumann, G. and Peters, J. (2014):
Learning to Predict Phases of Manipulation Tasks as Hidden States.
In: Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA), [Online-Edition: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=690...],
[Conference or Workshop Item]

Dann, C. and Neumann, G. and Peters, J. (2014):
Policy Evaluation with Temporal Differences: A Survey and Comparison.
In: Journal of Machine Learning Research 15 (2014) 809-883, pp. 809-883, 15, (March), [Online-Edition: http://jmlr.org/papers/volume15/dann14a/dann14a.pdf],
[Article]

Gomez, V. and Kappen, B. and Peters, J. and Neumann, G. (2014):
Policy Search for Path Integral Control.
In: European Conference on Machine Learning (ECML), Nancy, 15.-19. September 2014, [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Publications/Gomez_EC...],
[Conference or Workshop Item]

Rueckert, E. and Mindt, M. and Peters, J. and Neumann, G. (2014):
Robust Policy Updates for Stochastic Optimal Control.
In: International Conference on Humanoid Robots (HUMANOIDS), Madrid, November 18-20th, 2014, [Online-Edition: http://www.ias.informatik.tu-darmstadt.de/uploads/Site/EditP...],
[Conference or Workshop Item]

Lioutikov, R. and Paraschos, A. and Peters, J. and Neumann, G. (2014):
Sample-Based Information-Theoretic Stochastic Optimal Control.
In: IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 31 - June 7, 2014, [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Team/RudolfLioutikov/...],
[Conference or Workshop Item]

Daniel, C. and Neumann, G. and Peters, J. (2013):
Autonomous Reinforcement Learning with Hierarchical REPS.
In: International Joint Conference on Neural Networks (IJCNN), Dallas, Texas, USA, Aug 4, 2013 - Aug 9, 2013, [Conference or Workshop Item]

Kupcsik, A. G. and Deisenroth, M. P. and Peters, J. and Neumann, G. (2013):
Data-Efficient Generalization of Robot Skills with Contextual Policy Search.
In: Proceedings of the National Conference on Artificial Intelligence (AAAI), Bellevue, Washington, USA, 14–18 July 2013, [Online-Edition: http://www.ias.informatik.tu-darmstadt.de/uploads/Publicatio...],
[Conference or Workshop Item]

Neumann, G. and Kupcsik, A. G. and Deisenroth, M. P. and Peters, J. (2013):
Information-Theoretic Motor Skill Learning.
In: AAAI Workshop - Technical Report, AAAI Press, In: 2013 AAAI Workshop, Bellevue, WA, USA, WS-13-10, [Conference or Workshop Item]

Daniel, C. and Neumann, G. and Kroemer, O. and Peters, J. (2013):
Learning Sequential Motor Tasks.
In: Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, May 6-10, 2013, [Online-Edition: http://www.ias.informatik.tu-darmstadt.de/uploads/Publicatio...],
[Conference or Workshop Item]

Paraschos, A. and Neumann, G. and Peters, J. (2013):
A Probabilistic Approach to Robot Trajectory Generation.
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), [Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Publications/Parascho...],
[Conference or Workshop Item]

Paraschos, A. and Daniel, C. and Peters, J. and Neumann, G.
Burges, C. J. C. and Bottou, L. and Welling, M. and Ghahramani, Z. and Weinberger, K. Q. (eds.) (2013):
Probabilistic Movement Primitives.
In: Advances in Neural Information Processing Systems (NIPS), Lake Tahoe, Nevada, USA, 5-10 December 2013, In: Advances in Neural Information Processing Systems, 26, [Online-Edition: https://dblp.org/db/conf/nips/nips2013],
[Conference or Workshop Item]

Deisenroth, M. P. and Neumann, G. and Peters, J. (2013):
A Survey on Policy Search for Robotics.
In: Foundations and Trends in Robotics, Foundations and Trends R © in Robotics Vol. 2, Nos. 1–2 (2011) 1–142 c ©, pp. 388-403, 2, (1-2), DOI: 10.1561/2300000021,
[Online-Edition: http://www.ias.tu-darmstadt.de/uploads/Site/EditPublication/...],
[Article]

Peters, J. and Kober, J. and Muelling, K. and Kroemer, O. and Neumann, G. (2013):
Towards Robot Skill Learning: From Simple Skills to Table Tennis.
In: European Conference on Machine Learning (ECML), Nectar Track, Prag, September 23-27, 2013, [Online-Edition: http://www.ias.informatik.tu-darmstadt.de/publications/peter...],
[Conference or Workshop Item]

Ben Amor, H. and Kroemer, O. and Hillenbrand, U. and Neumann, G. and Peters, J. (2012):
Generalization of Human Grasping for Multi-Fingered Robot Hands.
In: Proceedings of the International Conference on Robot Systems (IROS), [Online-Edition: http://www.ias.informatik.tu-darmstadt.de/uploads/Publicatio...],
[Conference or Workshop Item]

Daniel, C. and Neumann, G. and Peters, J. (2012):
Hierarchical Relative Entropy Policy Search.
In: International Conference on Artificial Intelligence and Statistics (AISTATS 2012), La Palma, Canary Islands, April 21-23, 2012, [Online-Edition: https://www.aistats.org/aistats2012/],
[Conference or Workshop Item]

Daniel, C. and Neumann, G. and Peters, J. (2012):
Learning Concurrent Motor Skills in Versatile Solution Spaces.
In: Proceedings of the International Conference on Robot Systems (IROS), [Online-Edition: http://www.ias.informatik.tu-darmstadt.de/uploads/Publicatio...],
[Conference or Workshop Item]

Neumann, G. and Peters, J. (2009):
Fitted Q-iteration by Advantage Weighted Regression.
In: Advances in Neural Information Processing Systems 22 (NIPS 2008), Cambridge, MA: MIT Press, In: Spotlight Presentation � Acceptance Rate: 9.2%, [Conference or Workshop Item]

Pfohl, H.-Chr. and Elbert, R. and Schönberger, R.
Inderfurth, K. and Neumann, G. and Schenk, M. and Wäscher, G. and Ziems, D. (eds.) (2008):
Management von Logistik-Clustern: Eine Analyse der Vorteilhaftigkeit regionaler Kooperationen in globalen Logistiknetzwerken.
In: Netzwerklogistik, Magdeburg, pp. 107-122, [Book Section]

Kandeler, E. and Haase, S. and Deiglmayr, K. and Ruess, Liliane and Marhan, Sven and Neumann, G. and Römheld. V., and Bonkowski, Michael and Philippot, L. (2005):
Small-scale distribution of soil microbial communities and enzyme processes in the rhizosphere.
In: International Biomicrocosmos Workshop - for the Enhancement of Rhizosphere Research, Creative Research Initiative Sousei (CRIS) <2005, Sapporo>: Abstracts, [Conference or Workshop Item]

Pfohl, H.-Chr. and Elbert, R.
Wäscher, G. and Inderfurth, K. and Neumann, G. and Schenk, M. and Ziems, D. (eds.) (2005):
Komplexitätsbeherrschung in der Planung durch den Menschen oder IT/DV-Systeme? Ergebnisse einer Expertenbefragung zur Planung von Produktions- und Logistikprozessen.
In: Intelligente Logistikprozesse. Konzepte, Lösungen, Erfahrungen., Magdeburg, pp. 210-224, [Book Section]

Daniel, C. and Neumann, G. and Kroemer, O. and Peters, J. (2000):
Hierarchical Relative Entropy Policy Search.
In: Journal of Machine Learning Research, pp. 1-48, 1, [Online-Edition: http://www.ausy.tu-darmstadt.de/uploads/Site/EditPublication...],
[Article]

This list was generated on Sat Oct 19 02:21:22 2019 CEST.