Contact

Prof. Dr. (USC, USA) Jan Peters

Adresse: Spemannstr. 38
72076 Tübingen
Raum Nummer: 239
Tel.: 07071 601 585
Fax: 07071 601 552
E-Mail: jan.peters

 

Bild von Peters, Jan, Prof. Dr. (USC, USA)

Jan Peters

Position: Seniorwissenschaftler  Abteilung: Schölkopf

While I remain affliated with MPI as an adjunct scientist, I am now also a full professor at Technische Universität Darmstadt (TU Darmstadt).

My research centers around the goal of bringing advanced motor skills to robotics using techniques from machine learning. You can check out my research interests and my publications for further information on my private homepage.

For a reasonably formatted version of my publications see here.

More information on Jan Peters can be found on his private homepage and on his group's homepage.

 

 

Jan Peters is a full professor at Technische Universität Darmstadt (TU Darmstadt) heading the intelligent systems group while still being affliated with the MPI heading the robot learning lab as an adjunct scientist.

Jan Peters joined the Max-Planck Institute for Biological Cybernetics in April 2007 as a research scientist. Before joining MPI, Jan Peters studied Electrical Engineering, Computer Science and Mechanical Engineering. He graduated from the University of Hagen in 2000 with a Diplom-Informatiker (German M.Sc. in Computer Science) and from Munich University of Technology in 2001 with a Diplom-Ingenieur in Electrical Engineering (German M.Sc. in Electrical Engineering). In 2000-2001, he spent two semesters as visiting student at National University of Singapore. In 2002, he completed a M.Sc. in Computer Science and, in 2005, a M.S. in Mechanical Engineering both from USC. He joined USC's Computer Science Ph.D. program and the CLMC Lab in Fall 2001. Jan Peters has been a visiting research student at the Department of Robotics at the German Aerospace Research Center in Germany, at Siemens Advanced Engineering in Singapore and at the Department of Humanoid Robotics and Computational Neuroscience at the Advanded Telecommunication Research (ATR) Center in Japan. Jan Peters graduated from University of Southern California with a Ph.D. in Computer Science in March 2007. He remains affiliated with the CLMC Lab as an adjunct researcher.

More information on Jan Peters can be found on his private homepage.

Präferenzen: 
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Bücher (2):

Sigaud O und Peters J: From Motor Learning to Interaction Learning in Robots, 538, Springer, Berlin, Germany, (Januar-2010). ISBN: 978-3-642-05180-7, Series: Studies in Computational Intelligence ; 264
Peters J: Machine Learning for Robotics: Learning Methods for Robot Motor Skills, 107, VDM-Verlag, Saarbrücken, Germany, (Mai-2008). ISBN: 978-3-639-02110-3

Tagungsbände (1):

Lespérance Y, Lakemeyer G, Peters J und Pirri F: CogRob 2008: The 6th International Cognitive Robotics Workshop, 6th International Cognitive Robotics Workshop (CogRob 2008), 35, Patras University Press, Patras, Greece, (Juli-2008).
978-960-6843-09-9

Artikel (36):

Muelling K, Boularias A, Mohler B, Schölkopf B und Peters J (Oktober-2014) Learning strategies in table tennis using inverse reinforcement learning Biological Cybernetics 108(5) 603-619.
Kober J, Wilhelm A, Oztop E und Peters J (November-2012) Reinforcement learning to adjust parametrized motor primitives to new situations Autonomous Robots 33(4) 361-379.
Nguyen-Tuong D und Peters J (August-2012) Online Kernel-based Learning for Task-Space Tracking Robot Control IEEE Transactions on Neural Networks and Learning Systems 23(9) 1417-1425.
Lampert CH und Peters J (März-2012) Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components Journal of Real-Time Image Processing 7(1) 31-41.
pdf
Hachiya H, Peters J und Sugiyama M (November-2011) Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning Neural Computation 23(11) 2798-2832.
pdf
Mülling K, Kober J und Peters J (Oktober-2011) A biomimetic approach to robot table tennis Adaptive Behavior 19(5) 359-376.
Kober J und Peters J (Juli-2011) Policy Search for Motor Primitives in Robotics Machine Learning 84(1-2) 171-203.
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Gomez Rodriguez M, Peters J, Hill J, Schölkopf B, Gharabaghi A und Grosse-Wentrup M (Juni-2011) Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery Journal of Neural Engineering 8(3) 1-12.
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Kroemer O, Lampert CH und Peters J (Juni-2011) Learning Dynamic Tactile Sensing with Robust Vision-based Training IEEE Transactions on Robotics 27(3) 545-557.
Nguyen-Tuong D und Peters J (Mai-2011) Incremental online sparsification for model learning in real-time robot control Neurocomputing 74(11) 1859-1867.
Nguyen-Tuong D und Peters J (April-2011) Model learning for robot control: a survey Cognitive Processing 12(4) 319-340.
Detry R, Kraft D, Kroemer O, Peters J, Krüger N und Piater J (März-2011) Learning grasp affordance densities Paladyn: Journal of Behavioral Robotics 2(1) 1-17.
Piater J, Jodogne S, Detry R, Kraft D, Krüger N, Kroemer O und Peters J (Februar-2011) Learning Visual Representations for Perception-Action Systems International Journal of Robotics Research 30(3) 294-307.
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Peters J, Kober J und Schaal S (Dezember-2010) Algorithmen zum Automatischen Erlernen von Motorfähigkeiten at - Automatisierungstechnik 58(12) 688-694.
Peters J (November-2010) Policy gradient methods Scholarpedia 5(11) 3698.
Wierstra D, Förster A, Peters J und Schmidhuber J (Oktober-2010) Recurrent Policy Gradients Logic Journal of the IGPL 18(5) 620-634.
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Kroemer O, Detry R, Piater J und Peters J (September-2010) Combining active learning and reactive control for robot grasping Robotics and Autonomous Systems 58(9) 1105-1116.
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Kober J und Peters J (Juni-2010) Imitation and Reinforcement Learning IEEE Robotics and Automation Magazine 17(2) 55-62.
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Sehnke F, Osendorfer C, Rückstiess T, Graves A, Peters J und Schmidhuber J (Mai-2010) Parameter-exploring policy gradients Neural Networks 21(4) 551-559.
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Morimura T, Uchibe E, Yoshimoto J, Peters J und Doya K (Februar-2010) Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning Neural Computation 22(2) 342-376.
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Hachiya H, Akiyama T, Sugiyama M und Peters J (Dezember-2009) Adaptive Importance Sampling for Value Function Approximation in Off-policy Reinforcement Learning Neural Networks 22(10) 1399-1410.
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Nguyen-Tuong D, Seeger M und Peters J (November-2009) Model Learning with Local Gaussian Process Regression Advanced Robotics 23(15) 2015-2034.
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Peters J, Morimoto J, Tedrake R und Roy N (September-2009) Robot Learning IEEE Robotics and Automation Magazine 16(3) 19-20.
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Peters J und Ng AY (August-2009) Guest editorial: Special issue on robot learning, Part B Autonomous Robots 27(2) 91-92.
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Peters J und Kober J (August-2009) Policy Search for Motor Primitives KI - Zeitschrift Künstliche Intelligenz 23(3) 38-40.
Peters J und Ng AY (Juli-2009) Guest editorial: Special issue on robot learning, Part A Autonomous Robots 27(1) 1-2.
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Deisenroth MP, Rasmussen CE und Peters J (März-2009) Gaussian Process Dynamic Programming Neurocomputing 72(7-9) 1508-1524.
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Peters J (November-2008) Machine Learning for Motor Skills in Robotics Künstliche Intelligenz 2008(4) 41-43.
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Nakanishi J, Cory R, Mistry M, Peters J und Schaal S (Juni-2008) Operational Space Control: A Theoretical and Empirical Comparison International Journal of Robotics Research 27(6) 737-757.
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Peters J und Schaal S (Mai-2008) Reinforcement Learning of Motor Skills with Policy Gradients Neural Networks 21(4) 682-697.
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Steinke F, Hein M, Peters J und Schölkopf B (April-2008) Manifold-valued Thin-plate Splines with Applications in Computer Graphics Computer Graphics Forum 27(2) 437-448.
Peters J und Schaal S (März-2008) Natural Actor-Critic Neurocomputing 71(7-9) 1180-1190.
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Peters J und Schaal S (Februar-2008) Learning to Control in Operational Space International Journal of Robotics Research 27(2) 197-212.
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Peters J, Mistry M, Udwadia F, Nakanishi J und Schaal S (Oktober-2007) A unifying framework for robot control with redundant DOFs Autonomous Robots 24(1) 1-12.
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Peters J (September-2007) Book Review: Computational Intelligence: Principles, Techniques and Applications by Amit Konar The Computer Journal 50(6) 758-758.
Peters J (November-1998) Book Review: An Introduction to Fuzzy Logic for Practical Applications Künstliche Intelligenz (KI) 98(4) 60-60.

Beiträge zu Tagungsbänden (93):

Peters J, Mülling K und Kober J (2014) Experiments with Motor Primitives to learn Table Tennis In: Experimental Robotics, , 12th International Symposium on Experimental Robotics (ISER 2010), Springer, Berlin, Germany, 347-359.
Mülling K, Boularias A, Mohler B, Schölkopf B und Peters J (September-27-2013) Inverse Reinforcement Learning for Strategy Extraction, ECML PKDD 2013 Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 2013), 1-9.
pdf
Wang Z, Deisenroth MP, Ben Amor H, Vogt D, Schölkopf B und Peters J (Juli-2013) Probabilistic Modeling of Human Movements for Intention Inference In: Robotics: Science and Systems VIII, , 2012 Robotics: Science and Systems Conference, MIT Press, Cambridge, MA, USA, 433-440.
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Peters J, Mülling K, Kober J, Nguyen-Tuong D und Krömer O (August-2012) Robot Skill Learning, 20th European Conference on Artificial Intelligence (ECAI 2012), IOS Press, Amsterdam, Netherlands, 40-45.
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Kroemer O, Ugur E, Oztop E und Peters J (Mai-2012) A Kernel-based Approach to Direct Action Perception, IEEE International Conference on Robotics and Automation (ICRA 2012), IEEE, Piscataway, NJ, USA, 2605-2610.
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Bócsi B, Hennig P, Csató L und Peters J (Mai-2012) Learning Tracking Control with Forward Models, IEEE International Conference on Robotics and Automation (ICRA 2012), IEEE, Piscataway, NJ, USA, 259-264.
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Daniel C, Neumann G und Peters J (April-2012) Hierarchical Relative Entropy Policy Search, Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012), International Machine Learning Society, Madison, WI, USA, 273-281, Series: JMLR Workshop and Conference Proceedings ; 22.
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Kroemer O und Peters J (Januar-2012) A Non-Parametric Approach to Dynamic Programming In: Advances in Neural Information Processing Systems 24, , Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Curran, Red Hook, NY, USA, 1719-1727.
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Wang Z, Lampert CH, Mülling K, Schölkopf B und Peters J (September-2011) Learning anticipation policies for robot table tennis, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), IEEE, Piscataway, NJ, USA, 332-337.
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Kober J und Peters J (September-2011) Learning elementary movements jointly with a higher level task, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), IEEE, Piscataway, NJ, USA, 338-343.
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Bocsi B, Nguyen-Tuong D, Csato L, Schölkopf B und Peters J (September-2011) Learning inverse kinematics with structured prediction, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), IEEE, Piscataway, NJ, USA, 698-703.
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Last updated: Montag, 22.05.2017