Jan Peters

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Gerhard NeumannProfessor, Karlsruhe Institute of Technology (KIT)Verified email at robot-learning.de
Jens KoberAssociate Professor, CoR, TU DelftVerified email at tudelft.nl
Stefan SchaalRobotics, Machine Learning, AI, NeuroscienceVerified email at google.com
Oliver KroemerCarnegie Mellon University - The Robotics InstituteVerified email at andrew.cmu.edu
Marc DeisenrothUniversity College LondonVerified email at ucl.ac.uk
Duy Nguyen-TuongBosch Center for AI, GermanyVerified email at robot-learning.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Katharina MuellingRoboticistVerified email at google.com
Guilherme Jorge MaedaPreferred Networks Inc.Verified email at preferred.jp
Marco EwertonPostdoctoral researcher at Idiap Research Institute, SwitzerlandVerified email at idiap.ch
Rudolf LioutikovAssitant Professor of Practice, University of Texas at AustinVerified email at utexas.edu
Roberto CalandraFacebook AI ResearchVerified email at fb.com
Joni PajarinenAssistant Professor at Aalto University and Research Group Leader at IAS at TU DarmstadtVerified email at aalto.fi
Christian DanielBosch Center for Artificial IntelligenceVerified email at ias.tu-darmstadt.de
Herke van HoofUniversity of Amsterdam (UVA)Verified email at uva.nl
Alexandros ParaschosVolkswagen AGVerified email at argmax.ai
Jun NakanishiMeijo University, JapanVerified email at meijo-u.ac.jp
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinVerified email at amazon.de
Heni Ben AmorArizona State UniversityVerified email at asu.edu
Moritz Grosse-WentrupUniversity of ViennaVerified email at univie.ac.at

Jan Peters

Professor for Intelligent Autonomous Systems at Technische Universität Darmstadt

Verified email at ias.tu-darmstadt.de - Homepage

Robot Learning Reinforcement Learning Machine Learning Robotics Biomimetic Systems


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Reinforcement learning in robotics: A survey J Kober, JA Bagnell, J Peters The International Journal of Robotics Research 32 (11), 1238-1274, 2013	2402	2013
Reinforcement learning of motor skills with policy gradients J Peters, S Schaal Neural networks 21 (4), 682-697, 2008	967	2008
A survey on policy search for robotics MP Deisenroth, G Neumann, J Peters Foundations and trends in Robotics 2 (1-2), 388-403, 2013	930	2013
Natural actor-critic J Peters, S Schaal Neurocomputing 71 (7-9), 1180-1190, 2008	882	2008
Policy search for motor primitives in robotics J Kober, J Peters Machine Learning 84 (1), 171–203, 2011	751	2011
Natural evolution strategies D Wierstra, T Schaul, T Glasmachers, Y Sun, J Peters, J Schmidhuber The Journal of Machine Learning Research 15 (1), 949-980, 2014	621	2014
Policy gradient methods for robotics J Peters, S Schaal Proceedings of the IEEE/RSJ International Conference on Intelligent Robots …, 2006	609	2006
Relative entropy policy search J Peters, K Mülling, Y Altun Proceedings of the Twenty-fourth National Conference on Artificial …, 2010	579	2010
Model learning for robot control: a survey D Nguyen-Tuong, J Peters Cognitive processing 12 (4), 319-340, 2011	469	2011
Reinforcement learning for humanoid robotics J Peters, S Vijayakumar, S Schaal Proceedings of the 3rd IEEE-RAS International Conference on Humanoid Robots …, 2003	462	2003
Learning movement primitives S Schaal, J Peters, J Nakanishi, A Ijspeert Proceedings of the International Symposium on Robotics Research (ISRR), 561-572, 2005	430	2005
Learning to select and generalize striking movements in robot table tennis K Mülling, J Kober, O Kroemer, J Peters The International Journal of Robotics Research 32 (3), 263-279, 2013	398	2013
Probabilistic movement primitives A Paraschos, C Daniel, J Peters, G Neumann Advances in neural information processing systems, 2013	390	2013
Operational space control: A theoretical and empirical comparison J Nakanishi, R Cory, M Mistry, J Peters, S Schaal The International Journal of Robotics Research 27 (6), 737-757, 2008	371	2008
An algorithmic perspective on imitation learning T Osa, J Pajarinen, G Neumann, JA Bagnell, P Abbeel, J Peters arXiv preprint arXiv:1811.06711, 2018	335	2018
Model learning with local gaussian process regression D Nguyen-Tuong, M Seeger, J Peters Advanced Robotics 23 (15), 2015-2034, 2009	309	2009
Relative entropy inverse reinforcement learning A Boularias, J Kober, J Peters 14th International Conference on Artificial Intelligence and Statistics …, 2011	308	2011
Natural actor-critic J Peters, S Vijayakumar, S Schaal European Conference on Machine Learning, 280-291, 2005	279	2005
Parameter-exploring policy gradients F Sehnke, C Osendorfer, T Rückstieß, A Graves, J Peters, J Schmidhuber Neural Networks 23 (4), 551-559, 2010	268	2010
Gaussian process dynamic programming MP Deisenroth, CE Rasmussen, J Peters Neurocomputing 72 (7-9), 1508-1524, 2009	251	2009

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