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 |