2009 | ||
---|---|---|
41 | EE | Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters: Gaussian process dynamic programming. Neurocomputing 72(7-9): 1508-1524 (2009) |
2008 | ||
40 | Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama, Jan Peters: Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation. AAAI 2008: 1351-1356 | |
39 | EE | Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Bernhard Schölkopf: Learning Inverse Dynamics: a Comparison. ESANN 2008: 13-18 |
38 | EE | Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters: Model-Based Reinforcement Learning with Continuous States and Actions. ESANN 2008: 19-24 |
37 | EE | Jan Peters, Jens Kober, Duy Nguyen-Tuong: Policy Learning - A Unified Perspective with Applications in Robotics. EWRL 2008: 220-228 |
36 | EE | Frank Sehnke, Christian Osendorfer, Thomas Rückstieß, Alex Graves, Jan Peters, Jürgen Schmidhuber: Policy Gradients with Parameter-Based Exploration for Control. ICANN (1) 2008: 387-396 |
35 | EE | Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber: Episodic Reinforcement Learning by Logistic Reward-Weighted Regression. ICANN (1) 2008: 407-416 |
34 | EE | Jan Peters, Duy Nguyen-Tuong: Real-time learning of resolved velocity control on a Mitsubishi PA-10. ICRA 2008: 2872-2877 |
33 | EE | Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber: Natural Evolution Strategies. IEEE Congress on Evolutionary Computation 2008: 3381-3387 |
32 | EE | Duy Nguyen-Tuong, Jan Peters: Local Gaussian process regression for real-time model-based robot control. IROS 2008: 380-385 |
31 | EE | Jens Kober, Betty J. Mohler, Jan Peters: Learning perceptual coupling for motor primitives. IROS 2008: 834-839 |
30 | EE | Gerhard Neumann, Jan Peters: Fitted Q-iteration by Advantage Weighted Regression. NIPS 2008: 1177-1184 |
29 | EE | Duy Nguyen-Tuong, Matthias Seeger, Jan Peters: Local Gaussian Process Regression for Real Time Online Model Learning. NIPS 2008: 1193-1200 |
28 | EE | Silvia Chiappa, Jens Kober, Jan Peters: Using Bayesian Dynamical Systems for Motion Template Libraries. NIPS 2008: 297-304 |
27 | EE | Jens Kober, Jan Peters: Policy Search for Motor Primitives in Robotics. NIPS 2008: 849-856 |
26 | EE | Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber: Fitness Expectation Maximization. PPSN 2008: 337-346 |
25 | EE | Jan Peters, Michael Mistry, Firdaus E. Udwadia, Jun Nakanishi, Stefan Schaal: A unifying framework for robot control with redundant DOFs. Auton. Robots 24(1): 1-12 (2008) |
24 | EE | Florian Steinke, Matthias Hein, Jan Peters, Bernhard Schölkopf: Manifold-valued Thin-Plate Splines with Applications in Computer Graphics. Comput. Graph. Forum 27(2): 437-448 (2008) |
23 | EE | Jan Peters, Stefan Schaal: Reinforcement learning of motor skills with policy gradients. Neural Networks 21(4): 682-697 (2008) |
22 | EE | Jan Peters, Stefan Schaal: Natural Actor-Critic. Neurocomputing 71(7-9): 1180-1190 (2008) |
2007 | ||
21 | EE | Jan Peters, Stefan Schaal, Bernhard Schölkopf: Towards Machine Learning of Motor Skills. AMS 2007: 138-144 |
20 | EE | Jan Peters, Stefan Schaal: Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning. ESANN 2007: 295-300 |
19 | EE | Guntram Flach, Stefan Audersch, Jan Peters: Integration von mobilen Agenten und Webservice-basierten Workflows innerhalb komplexer eGovernment-Prozesse. Grundlagen von Datenbanken 2007: 17-21 |
18 | EE | Daan Wierstra, Alexander Förster, Jan Peters, Jürgen Schmidhuber: Solving Deep Memory POMDPs with Recurrent Policy Gradients. ICANN (1) 2007: 697-706 |
17 | EE | Jan Peters, Stefan Schaal: Reinforcement learning by reward-weighted regression for operational space control. ICML 2007: 745-750 |
16 | EE | Jan Peters, Stefan Schaal: Policy Learning for Motor Skills. ICONIP (2) 2007: 233-242 |
15 | EE | Jan Peters, Stefan Schaal: Reinforcement Learning for Operational Space Control. ICRA 2007: 2111-2116 |
14 | EE | Jun Nakanishi, Michael Mistry, Jan Peters, Stefan Schaal: Towards compliant humanoids-an experimental assessment of suitable task space position/orientation controllers. IROS 2007: 2520-2527 |
13 | EE | Jan Peters: Computational Intelligence: Principles, Techniques and Applications. Comput. J. 50(6): 758 (2007) |
12 | EE | Jan Peters, Roland Rieke, Taufiq Rochaeli, Björn Steinemann, Ruben Wolf: A Holistic Approach to Security Policies - Policy Distribution with XACML over COPS. Electr. Notes Theor. Comput. Sci. 168: 143-157 (2007) |
2006 | ||
11 | EE | Jan Peters, Stefan Schaal: Reinforcement Learning for Parameterized Motor Primitives. IJCNN 2006: 73-80 |
10 | EE | Jan Peters, Stefan Schaal: Policy Gradient Methods for Robotics. IROS 2006: 2219-2225 |
9 | EE | Jo-Anne Ting, Michael Mistry, Jan Peters, Stefan Schaal, Jun Nakanishi: A Bayesian Approach to Nonlinear Parameter Identification for Rigid Body Dynamics. Robotics: Science and Systems 2006 |
8 | EE | Jan Peters, Stefan Schaal: Learning Operational Space Control. Robotics: Science and Systems 2006 |
2005 | ||
7 | Jan Peters, Bastian Emig, Marten Jung, Stefan Schmidt: Prediction of Delays in Public Transportation using Neural Networks. CIMCA/IAWTIC 2005: 92-97 | |
6 | EE | Jan Peters, Sethu Vijayakumar, Stefan Schaal: Natural Actor-Critic. ECML 2005: 280-291 |
5 | EE | Volker Roth, Ulrich Pinsdorf, Jan Peters: A distributed content-based search engine based on mobile code. SAC 2005: 66-73 |
2004 | ||
4 | EE | Piklu Gupta, Mario Hoffmann, Bernhard Holtkamp, Wiebke Möhr, Jan Peters, Matthias Ritscher, Agnès Voisard: Mobile kontextabhängige Multimediadienste. Informatik Spektrum 27(1): 35-43 (2004) |
2003 | ||
3 | EE | Stefan Schaal, Jan Peters, Jun Nakanishi, Auke Jan Ijspeert: Learning Movement Primitives. ISRR 2003: 561-572 |
2002 | ||
2 | Jan Peters, P. Patrick van der Smagt: Searching a Scalable Approach to Cerebellar Based Control. Appl. Intell. 17(1): 11-33 (2002) | |
2001 | ||
1 | EE | Volker Roth, Jan Peters: A Scalable and Secure Global Tracking Service for Mobile Agents. Mobile Agents 2001: 169-181 |