Jan Peters

发表

Natural Actor-Critic

Stefan Schaal, Sethu Vijayakumar, Jan Peters, 2003, Neurocomputing.

A Survey on Policy Search for Robotics

Jan Peters, Gerhard Neumann, Marc Peter Deisenroth, 2013, Found. Trends Robotics.

Learning modular policies for robotics

Jan Peters, Alexandros Paraschos, Christian Daniel, 2014, Front. Comput. Neurosci..

Policy Gradient Methods for Robotics

Stefan Schaal, Jan Peters, Jan Peters, 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Reinforcement Learning for Humanoid Robotics

Stefan Schaal, Sethu Vijayakumar, Jan Peters, 2003 .

Reinforcement learning by reward-weighted regression for operational space control

Stefan Schaal, Jan Peters, Jan Peters, 2007, ICML '07.

Policy Gradient Methods

Jan Peters, J. Andrew Bagnell, Jan Peters, 2010, Encyclopedia of Machine Learning.

Episodic Future Thinking Reduces Reward Delay Discounting through an Enhancement of Prefrontal-Mediotemporal Interactions

Jan Peters, C. Büchel, 2010, Neuron.

Relative Entropy Policy Search

Yasemin Altun, Jan Peters, Katharina Mülling, 2010 .

Gaussian process dynamic programming

Carl E. Rasmussen, Jan Peters, Marc Peter Deisenroth, 2009, Neurocomputing.

Reinforcement learning in robotics: A survey

Jan Peters, J. Andrew Bagnell, Jens Kober, 2013, Int. J. Robotics Res..

Learning motor primitives for robotics

Jan Peters, Jens Kober, Jan Peters, 2009, 2009 IEEE International Conference on Robotics and Automation.

Learning sequential motor tasks

Oliver Kroemer, Jan Peters, Christian Daniel, 2013, 2013 IEEE International Conference on Robotics and Automation.

Active Reward Learning

Oliver Kroemer, Jan Peters, Christian Daniel, 2014, Robotics: Science and Systems.

A unifying methodology for the control of robotic systems

Jun Nakanishi, Stefan Schaal, Jan Peters, 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Comparative experiments on task space control with redundancy resolution

Jun Nakanishi, Stefan Schaal, Jan Peters, 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Relative Entropy Inverse Reinforcement Learning

Jan Peters, Abdeslam Boularias, Jens Kober, 2011, AISTATS.

Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot

Oliver Kroemer, Jan Peters, Guilherme Maeda, 2014, IAS.

Bayesian optimization for learning gaits under uncertainty

Jan Peters, Marc Peter Deisenroth, André Seyfarth, 2015, Annals of Mathematics and Artificial Intelligence.

A Bayesian Approach to Nonlinear Parameter Identification for Rigid Body Dynamics

Jun Nakanishi, Stefan Schaal, Jan Peters, 2006, Robotics: Science and Systems.

Probabilistic inference for determining options in reinforcement learning

Jan Peters, Herke van Hoof, Christian Daniel, 2016, Machine Learning.

Fitness Expectation Maximization

Tom Schaul, Jürgen Schmidhuber, Jan Peters, 2008, PPSN.

Learning concurrent motor skills in versatile solution spaces

Jan Peters, Christian Daniel, Gerhard Neumann, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Learning strategies in table tennis using inverse reinforcement learning

Bernhard Schölkopf, Betty J. Mohler, Jan Peters, 2014, Biological Cybernetics.

Policy Search for Motor Primitives in Robotics

Jan Peters, Jens Kober, Jan Peters, 2008, NIPS 2008.

Policy Gradient Methods for Robot Control

Stefan Schaal, Sethu Vijayakumar, Jan Peters, 2003 .

Noname manuscript No. (will be inserted by the editor) Policy Search for Motor Primitives in Robotics

Jan Peters, Jens Kober, Jan Peters, 2022 .

Reinforcement Learning to Adjust Robot Movements to New Situations

Jan Peters, Jens Kober, Erhan Öztop, 2010, IJCAI.

Machine Learning for motor skills in robotics

Jan Peters, Jan Peters, 2008, Künstliche Intell..

Natural Actor-Critic

Stefan Schaal, Jan Peters, Jan Peters, 2003, Neurocomputing.

Learning robot in-hand manipulation with tactile features

Jan Peters, Herke van Hoof, Gerhard Neumann, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Solving Deep Memory POMDPs with Recurrent Policy Gradients

Jürgen Schmidhuber, Alexander Förster, Jan Peters, 2007, ICANN.

Learning of Non-Parametric Control Policies with High-Dimensional State Features

Jan Peters, Herke van Hoof, Gerhard Neumann, 2015, AISTATS.

Learning Movement Primitives

Jun Nakanishi, Stefan Schaal, Auke Jan Ijspeert, 2005, ISRR.

Reinforcement Learning for Parameterized Motor Primitives

Stefan Schaal, Jan Peters, Jan Peters, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Hierarchical Relative Entropy Policy Search

Jan Peters, Christian Daniel, Gerhard Neumann, 2014, AISTATS.

Recurrent policy gradients

Jürgen Schmidhuber, Alexander Förster, Jan Peters, 2010, Log. J. IGPL.

Fitted Q-iteration by Advantage Weighted Regression

Jan Peters, Gerhard Neumann, Jan Peters, 2008, NIPS.

Learning to Control in Operational Space

Stefan Schaal, Jan Peters, Jan Peters, 2008, Int. J. Robotics Res..

Learning to select and generalize striking movements in robot table tennis

Oliver Kroemer, Jan Peters, Katharina Mülling, 2012, AAAI Fall Symposium: Robots Learning Interactively from Human Teachers.

Natural Evolution Strategies

Tom Schaul, Jan Peters, Daan Wierstra, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Policy evaluation with temporal differences: a survey and comparison

Jan Peters, Gerhard Neumann, Christoph Dann, 2015, J. Mach. Learn. Res..

Trajectory planning for optimal robot catching in real-time

Gerd Hirzinger, Jan Peters, Duy Nguyen-Tuong, 2011, 2011 IEEE International Conference on Robotics and Automation.

Movement templates for learning of hitting and batting

Christoph H. Lampert, Bernhard Schölkopf, Oliver Kroemer, 2010, 2010 IEEE International Conference on Robotics and Automation.

Generalization of human grasping for multi-fingered robot hands

Oliver Kroemer, Jan Peters, Heni Ben Amor, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Learning Dynamic Tactile Sensing With Robust Vision-Based Training

Christoph H. Lampert, Oliver Kroemer, Jan Peters, 2011, IEEE Transactions on Robotics.

An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward

Nando de Freitas, Arnaud Doucet, Jan Peters, 2009, AISTATS.

Extracting low-dimensional control variables for movement primitives

Jan Peters, G. Neumann, A. Paraschos, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

Towards Motor Skill Learning for Robotics

Oliver Kroemer, Jan Peters, Katharina Mülling, 2007, ISRR.

Learning Operational Space Control

Stefan Schaal, Jan Peters, Jan Peters, 2006, Robotics: Science and Systems.

Probabilistic Movement Primitives

Jan Peters, Alexandros Paraschos, Christian Daniel, 2013, NIPS.

Nonamemanuscript No. (will be inserted by the editor) Reinforcement Learning to Adjust Parametrized Motor Primitives to

Jan Peters, Andreas Wilhelm, Jens Kober, 2011 .

A unifying framework for robot control with redundant DOFs

Jun Nakanishi, Stefan Schaal, Jan Peters, 2007, Auton. Robots.

Policy Search for Motor Primitives

Jan Peters, Jens Kober, Jan Peters, 2009, Künstliche Intell..

Toward fast policy search for learning legged locomotion

Jan Peters, Marc Peter Deisenroth, André Seyfarth, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Towards learning hierarchical skills for multi-phase manipulation tasks

Oliver Kroemer, Jan Peters, Herke van Hoof, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

Policy Gradients with Parameter-Based Exploration for Control

Frank Sehnke, Christian Osendorfer, Jürgen Schmidhuber, 2008, ICANN.

From Motor Learning to Interaction Learning in Robots

Olivier Sigaud, Jan Peters, Jan Peters, 2010, From Motor Learning to Interaction Learning in Robots.

Local Gaussian process regression for real-time model-based robot control

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Learning throwing and catching skills

Jan Peters, Katharina Mülling, Jens Kober, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Probabilistic movement modeling for intention inference in human–robot interaction

Bernhard Schölkopf, Jan Peters, Katharina Mülling, 2013, Int. J. Robotics Res..

Probabilistic model-based imitation learning

Peter Englert, Jan Peters, Alexandros Paraschos, 2013, Adapt. Behav..

Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies

Jan Peters, Gerhard Neumann, Takayuki Osa, 2016, ISER.

Learning robot tactile sensing for object manipulation

Oliver Kroemer, Yevgen Chebotar, Jan Peters, 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Domain Randomization for Simulation-Based Policy Optimization with Transferability Assessment

Jan Peters, Michael Gienger, Fabio Muratore, 2018, CoRL.

Learning walk and trot from the same objective using different types of exploration pdf

Jan Peters, Zinan Liu, Kai Ploeger, 2019, ArXiv.

A Non-Parametric Approach to Dynamic Programming

Oliver Kroemer, Jan Peters, Jan Peters, 2011, NIPS.

A Probabilistic Framework for Semi-autonomous Robots Based on Interaction Primitives with Phase Estimation

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2015, ISRR.

Adaptive importance sampling for value function approximation in off-policy reinforcement learning

Masashi Sugiyama, Jan Peters, Hirotaka Hachiya, 2009, Neural Networks.

Robot Skill Learning

Oliver Kroemer, Jan Peters, Katharina Mülling, 2012, ECAI.

Computed Torque Control with Nonparametric Regression Techniques

Jan Peters, M. Seeger, D. Nguyen-Tuong, 2008 .

Evaluation of tactile feature extraction for interactive object recognition

Jan Peters, Janine Hoelscher, Tucker Hermans, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Online Learning of an Open-Ended Skill Library for Collaborative Tasks

Jan Peters, Susanne Trick, Dorothea Koert, 2018, 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids).

Active Structured Learning for High-Speed Object Detection

Christoph H. Lampert, Jan Peters, Jan Peters, 2009, DAGM-Symposium.

Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots pdf

Jan Peters, Roberto Calandra, Dieter Büchler, 2019, Robotics Auton. Syst..

Model-free Inverse Reinforcement Learning

Jan Peters, Jens Kober, Abdeslam Boularias, 2011 .

HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints pdf

Jan Peters, Debora Clever, Michael Lutter, 2019, CoRL.

Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction

Jan Peters, Susanne Trick, Dorothea Koert, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Reinforcement learning vs human programming in tetherball robot games

Jan Peters, Simone Parisi, Hany Abdulsamad, 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Model-Based Quality-Diversity Search for Efficient Robot Learning

Jan Peters, Svenja Stark, Daniel Tanneberg, 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

In-Hand Object Stabilization by Independent Finger Control pdf

Jan Peters, Filipe Veiga, Benoni B. Edin, 2018, ArXiv.

Advances in Human-Robot Handshaking pdf

Jan Peters, Ruth Stock-Homburg, Vignesh Prasad, 2020, ICSR.

Russland in den Augen polnischer und deutscher Experten

Jan Peters, Agnieszka Łada, Jan Peters, 2010, RA 2010.

Evaluation of the Handshake Turing Test for anthropomorphic Robots

Jan Peters, Ruth Stock-Homburg, Katharina Schneider, 2020, HRI.

Adapting Preshaped Grasping Movements Using Vision Descriptors

Oliver Kroemer, Justus H. Piater, Jan Peters, 2010, SAB.

Multi-modal filtering for non-linear estimation

Jan Peters, Marc Peter Deisenroth, Sanket Kamthe, 2013, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Maximally informative interaction learning for scene exploration

Oliver Kroemer, Jan Peters, Herke van Hoof, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Developing biorobotics for veterinary research into cat movements

Agusti Solanas, Oskar von Stryk, Jan Peters, 2015 .

Whole-body multi-contact motion in humans and humanoids: Advances of the CoDyCo European project

Vincent Padois, Jan Peters, Serena Ivaldi, 2017, Robotics Auton. Syst..

Entropic Risk Measure in Policy Search

Jan Peters, Boris Belousov, David Nass, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

An Algorithmic Perspective on Imitation Learning

Pieter Abbeel, Jan Peters, J. Andrew Bagnell, 2018, Found. Trends Robotics.

Stabilizing novel objects by learning to predict tactile slip

Jan Peters, Herke van Hoof, Filipe Veiga, 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Policy Search for Path Integral Control

Vicenç Gómez, Hilbert J. Kappen, Jan Peters, 2014, ECML/PKDD.

Learning grasp affordance densities

Oliver Kroemer, Justus H. Piater, Dirk Kraft, 2011, Paladyn J. Behav. Robotics.

Parameter-exploring policy gradients

Frank Sehnke, Christian Osendorfer, Jürgen Schmidhuber, 2010, Neural Networks.

Control, Planning, Learning, and Imitation with Dynamic Movement Primitives

Jun Nakanishi, Stefan Schaal, Auke Jan Ijspeert, 2003 .

Operational Space Control: A Theoretical and Empirical Comparison

Jun Nakanishi, Stefan Schaal, Jan Peters, 2008, Int. J. Robotics Res..

Model learning for robot control: a survey

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2011, Cognitive Processing.

Using Bayesian Dynamical Systems for Motion Template Libraries

Jan Peters, Jens Kober, Silvia Chiappa, 2008, NIPS.

Combining active learning and reactive control for robot grasping

Oliver Kroemer, Justus H. Piater, Jan Peters, 2010, Robotics Auton. Syst..

Active learning using mean shift optimization for robot grasping

Oliver Kroemer, Justus H. Piater, Jan Peters, 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Probabilistic movement primitives for coordination of multiple human–robot collaborative tasks

Oliver Kroemer, Jan Peters, Guilherme Maeda, 2017, Auton. Robots.

Mobile monitoring for mapping spatial variation in urban air quality: Development and validation of a methodology based on an extensive dataset

Joris Van den Bossche, Jan Peters, B. Baets, 2015 .

A kernel-based approach to direct action perception

Oliver Kroemer, Jan Peters, Emre Ugur, 2012, 2012 IEEE International Conference on Robotics and Automation.

A biomimetic approach to robot table tennis

Jan Peters, Katharina Mülling, Jens Kober, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Model-based contextual policy search for data-efficient generalization of robot skills

Ai Poh Loh, Jan Peters, Gerhard Neumann, 2017, Artif. Intell..

A Computational Model of Human Table Tennis for Robot Application

Jan Peters, Katharina Mülling, Jan Peters, 2009, AMS.

An experimental comparison of Bayesian optimization for bipedal locomotion

Jan Peters, Marc Peter Deisenroth, André Seyfarth, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Simulating Human Table Tennis with a Biomimetic Robot Setup

Jan Peters, Katharina Mülling, Jens Kober, 2010, SAB.

Towards Robot Skill Learning: From Simple Skills to Table Tennis

Oliver Kroemer, Jan Peters, Katharina Mülling, 2013, ECML/PKDD.

Grasping with Vision Descriptors and Motor Primitives

Oliver Kroemer, Justus H. Piater, Jan Peters, 2010, ICINCO.

Probabilistic Modeling of Human Movements for Intention Inference

Bernhard Schölkopf, Jan Peters, Zhikun Wang, 2012, Robotics: Science and Systems.

A New Methodology for Robot Controller Design

Stefan Schaal, Jan Peters, Firdaus E. Udwadia, 2005 .

Using probabilistic movement primitives in robotics

Jan Peters, Alexandros Paraschos, Christian Daniel, 2017, Autonomous Robots.

Model Learning in Robotics: a Survey

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2011 .

A Unifying Framework for the Control of Robotic Systems

Jun Nakanishi, Stefan Schaal, Jan Peters, 2005 .

Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning pdf

Jan Peters, Michael Lutter, Christian Ritter, 2019, ICLR.

Active tactile object exploration with Gaussian processes

Jan Peters, Herke van Hoof, Filipe Veiga, 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks

Jan Peters, Elmar Rueckert, Daniel Tanneberg, 2018, Neural Networks.

Proceedings of the 10th European Workshop on Reinforcement Learning

Jan Peters, Marc Peter Deisenroth, C. S. Szepesvári, 2013 .

Underactuated Waypoint Trajectory Optimization for Light Painting Photography

Jan Peters, Boris Belousov, Fabio Muratore, 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

Experience Reuse with Probabilistic Movement Primitives

Jan Peters, Svenja Stark, Elmar Rueckert, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Visual Perception of Robot Movements – How Much Information Is Required?

Jan Peters, Josef Wiemeyer, Marco Ewerton, 2019, Proceedings of the 12th International Symposium on Computer Science in Sport (IACSS 2019).

Local-utopia policy selection for multi-objective reinforcement learning

Jan Peters, Simone Parisi, Tobias Viernickel, 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

Approximate Value Iteration Based on Numerical Quadrature

Jan Peters, Bastian Bischoff, Julia Vinogradska, 2018, IEEE Robotics and Automation Letters.

Local Online Motor Babbling: Learning Motor Abundance of a Musculoskeletal Robot Arm*

Koh Hosoda, Shuhei Ikemoto, Jan Peters, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Mean squared advantage minimization as a consequence of entropic policy improvement regularization

Jan Peters, B. Belousov, 2018 .

An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions pdf

Jan Peters, Riad Akrour, Samuele Tosatto, 2020, Stats.

A brain-robot interface for studying motor learning after stroke

Bernhard Schölkopf, Moritz Grosse-Wentrup, Jan Peters, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Dimensionality reduction for probabilistic movement primitives

Carme Torras, Jan Peters, Gerhard Neumann, 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

Manifold‐valued Thin‐Plate Splines with Applications in Computer Graphics

Bernhard Schölkopf, Florian Steinke, Matthias Hein, 2008, Comput. Graph. Forum.

ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows pdf

Jan Peters, Julen Urain, Davide Tateo, 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Learning optimal striking points for a ping-pong playing robot

Bernhard Schölkopf, Jan Peters, Yanlong Huang, 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Neural Signatures of Motor Skill in the Resting Brain

Bernhard Schölkopf, Moritz Grosse-Wentrup, Jan Peters, 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).

Predicting motor learning performance from Electroencephalographic data

Jan Peters, B. Schölkopf, T. Zander, 2014, Journal of NeuroEngineering and Rehabilitation.

A Unifying Computational Framework for Optimization and Dynamic Systems Approaches to Motor Control

Stefan Schaal, Auke Jan Ijspeert, Jan Peters, 2003 .

Anticipatory action selection for human-robot table tennis

Bernhard Schölkopf, Jan Peters, Katharina Mülling, 2017, Artif. Intell..

Perspectives on Sim2Real Transfer for Robotics: A Summary of the R: SS 2020 Workshop pdf

Kostas E. Bekris, C. Karen Liu, Ken Goldberg, 2020, ArXiv.

Computational Intelligence: Principles, Techniques and Applications

Jan Peters, Jan Peters, 2007, Comput. J..

The neural mechanisms of inter-temporal decision-making: understanding variability

Jan Peters, C. Büchel, 2011, Trends in Cognitive Sciences.

Building a Library of Tactile Skills Based on FingerVision

Jan Peters, Filipe Veiga, Boris Belousov, 2019, 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids).

Learning Vision-Based Tactile Skills for Robotic Architectural Assembly

Jan Peters, 2019 .

How Cognitive Models of Human Body Experience Might Push Robotics

Betty J. Mohler, Jan Peters, Philipp Beckerle, 2019, Front. Neurorobot..

Balancing Safety and Exploitability in Opponent Modeling

Jan Peters, Katharina Mülling, Zhikun Wang, 2011, AAAI.

Learning Motor Skills - From Algorithms to Robot Experiments

Jan Peters, Jens Kober, Jan Peters, 2013, Springer Tracts in Advanced Robotics.

Bayesian Regression for Artifact correction in Electroencephalography

Vinay Jayaram, Moritz Grosse-Wentrup, Jan Peters, 2017, GBCIC.

Receding Horizon Curiosity pdf

Jan Peters, Hany Abdulsamad, Boris Belousov, 2019, CoRL.

Catching heuristics are optimal control policies

Jan Peters, Gerhard Neumann, Constantin A. Rothkopf, 2016, NIPS.

Switched Latent Force Models for Movement Segmentation

Bernhard Schölkopf, Neil D. Lawrence, Jan Peters, 2010, NIPS.

Multi-agent active information gathering in discrete and continuous-state decentralized POMDPs by policy graph improvement

Jan Peters, Joni Pajarinen, Mikko Lauri, 2020, Autonomous Agents and Multi-Agent Systems.

Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling

Betty J. Mohler, Jan Peters, Jens Kober, 2010, From Motor Learning to Interaction Learning in Robots.

Numerical Quadrature for Probabilistic Policy Search

Jan Peters, Torsten Koller, Bastian Bischoff, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A flexible hybrid framework for modeling complex manipulation tasks

Oliver Kroemer, Jan Peters, Jan Peters, 2011, 2011 IEEE International Conference on Robotics and Automation.

Hybrid control trajectory optimization under uncertainty

Siddhartha S. Srinivasa, Jan Peters, Gerhard Neumann, 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Goal-driven dimensionality reduction for reinforcement learning

Jan Peters, Simone Parisi, Simon Ramstedt, 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Bayesian Gait Optimization for Bipedal Locomotion

Jan Peters, Marc Peter Deisenroth, André Seyfarth, 2014, LION.

Formal Comparison of Dual-Parameter Temporal Discounting Models in Controls and Pathological Gamblers

Christian Büchel, Jan Peters, Stephan F. Miedl, 2012, PloS one.

Efficient online adaptation with stochastic recurrent neural networks

Jan Peters, Daniel Tanneberg, Elmar A. Rückert, 2017, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids).

Prediction of Intention during Interaction with iCub with Probabilistic Movement Primitives

François Charpillet, Jan Peters, Serena Ivaldi, 2017, Front. Robot. AI.

A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning pdf

Jan Peters, Hany Abdulsamad, Pascal Klink, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Phase estimation for fast action recognition and trajectory generation in human–robot collaboration

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2017, Int. J. Robotics Res..

Robot Learning

Jun Morimoto, Jan Peters, Russ Tedrake, 2017, Encyclopedia of Machine Learning and Data Mining.

Bayesian Online Detection and Prediction of Change Points pdf

Stefan Bauer, Bernhard Schölkopf, Jan Peters, 2019, ArXiv.

Model-based imitation learning by probabilistic trajectory matching

Peter Englert, Jan Peters, Alexandros Paraschos, 2013, 2013 IEEE International Conference on Robotics and Automation.

Towards Engagement Models that Consider Individual Factors in HRI: On the Relation of Extroversion and Negative Attitude Towards Robots to Gaze and Speech During a Human–Robot Assembly Task

Mohamed Chetouani, Jan Peters, Serena Ivaldi, 2015, Int. J. Soc. Robotics.

Probabilistic Prioritization of Movement Primitives

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2017, IEEE Robotics and Automation Letters.

Integrating contrastive learning with dynamic models for reinforcement learning from images

Jan Peters, O. Arenz, Bang You, 2022, Neurocomputing.

Partially Unsupervised Deep Meta-Reinforcement Learning

Jan Peters, Fabio Muratore, Jonas Eschmann, 2021 .

Guided Reinforcement Learning Under Partial Observability

Jan Peters, J. Pajarinen, Tag der Einreichung, 2019 .

03 62 0 v 1 [ cs . L G ] 8 O ct 2 01 9 Receding Horizon Curiosity

Jan Peters, B. Belousov, Hany Abdulsamad, 2019 .

Hierarchical Learning of Motor Skills with Information-Theoretic Policy Search

Jan Peters, M. Deisenroth, G. Neumann, 2013 .

Reinforcement Learning with Bounded Information Loss

Jan Peters, Y. Altun, Katharina Muelling, 2011 .

Addressing the Correspondence Problem by Model-based Imitation Learning

Jan Peters, M. Deisenroth, A. Paraschos, 2013 .

Incremental Imitation Learning with Estimation of Uncertainty

Jan Peters, 2017 .

Risk-Sensitive Policy Search with Applications to Robot-Badminton

Jan Peters, 2018 .

Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities

Jan Peters, Elmar Rueckert, Jan Peters, 2016 .

Combining Human Demonstrations and Motion Planning for Movement Primitive Optimization

Jan Peters, Rudolf Lioutikov, Guilherme J. Maeda, 2016 .

Learning Probabilistic Classifiers from Electromyography Data for Predicting Knee Abnormalities

Jan Peters, Elmar Rueckert, Tag der Einreichung, 2016 .

Learning Probabilistic Feedforward and Feedback Policies for Stable Walking

Jan Peters, E. Rückert, Tag der Einreichung, 2016 .

Modeling Spatio-Temporal Variability in Human-Robot Interaction with Probabilistic Movement Primitives

Jan Peters, G. Neumann, Rudolf Lioutikov, 2015 .

Combination of Movement Primitives for Robotics Kombination von Movement Primitives in der Robotik

Jan Peters, G. Neumann, A. Paraschos, 2014 .

Modeling Human-Robot Interaction with Probabilistic Movement Representations

Jan Peters, G. Neumann, Guilherme J. Maeda, 2014 .

Data-Efficient Learning of Robotic Grasps From Human Preferences

Jan Peters, G. Neumann, Tag der Einreichung, 2017 .

Efficient Exploration using Value Bounds in Deep Reinforcement Learning Effiziente Exploration in Deep Reinforcement Learning mittels beschraenkter

Jan Peters, J. Pajarinen, 2019 .

Deep Learning of Inverse Dynamic Models

Jan Peters, M. Lutter, Christian Ritter, 2018 .

The Effects of Intrinsic Motivation Signals on Reinforcement Learning Strategies

Jan Peters, E. Rückert, Svenja Stark, 2018 .

Machine Learning for Active Gait Support with a Powered Ankle Prosthesis

Jan Peters, A. Seyfarth, Tag der Einreichung, 2014 .

Model Learning with Local Gaussian Process Regression

Jan Peters, Duy Nguyen-Tuong, Matthias W. Seeger, 2009, Adv. Robotics.

Deep Lagrangian Networks for Robot Control Deep Lagrangian Networks für Roboterregelung

Jan Peters, 2020 .

Learning a Multi-Task Model for Control of a Compliant Robot

Jan Peters, H. V. Hoof, M. Smyk, 2016 .

Bayesian optimization for learning gaits under uncertainty

Jan Peters, M. Deisenroth, R. Calandra, 2015, Annals of Mathematics and Artificial Intelligence.

Robot Learning Learning Models for Control

Jan Peters, M. Seeger, D. Nguyen-Tuong, 2009 .

Reinforcement Learning for Operational Space Control

Stefan Schaal, Jan Peters, Jan Peters, 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

Learning Robust Control Policies from Simulations with Perturbed Parameters

Jan Peters, Tag der Einreichung, Erklärung zur Master-Thesis, 2018 .

Non-Parametric Policy Learning for High-Dimensional State Representations

Jan Peters, G. Neumann, H. V. Hoof, 2015 .

Generalizing Manipulations using Vision Kernels

Jan Peters, Oliver Kroemer, E. Oztop, 2012 .

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos pdf

Carl E. Rasmussen, Jan Peters, Kenji Doya, 2019, ICML.

ProMPs Robot Trajectory Intention Prediction Belief Tracker Imitation Learning Intention Aware ProMP Adaptation Spatial Deformation Mode Temporal Scaling Mode Robot Goal Tracker Human observations Motion Goals Trajectory Predictions

Jan Peters, C. Rothkopf, Dorothea Koert, 2019 .

Benchmarking Reinforcement Learning Algorithms on Tetherball Games

Jan Peters, Hany Abdulsamad, Tag der Einreichung, 2018 .

Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning

Stefan Schaal, Jan Peters, Jan Peters, 2007, ESANN.

Self-Paced Domain Randomization

Jan Peters, Fabio Muratore, Fabian Damken, 2021 .

Infinite-Mixture Policies in Reinforcement Learning

Jan Peters, Tag der Einreichung, Erklärung zur Bachelor-Thesis, 2018 .

3 D Object Reconstruction from Partial Views

Jan Peters, Tag der Einreichung, Erklärung zur Master-Thesis, 2014 .

Policy gradient methods

Jan Peters, J. Andrew Bagnell, Jan Peters, 2010, Scholarpedia.

Robot Learning

Jun Morimoto, Nicholas Roy, Jan Peters, 2019, Encyclopedia of Machine Learning.

Adaptive importance sampling with automatic model selection in reward weighted regression (ニューロコンピューティング)

Masashi Sugiyama, Jan Peters, Hirotaka Hachiya, 2009 .

Motor Skill Learning for Humanoid Robots

Jan Peters, Jan Peters, 2005 .

Chance Constraints for Stochastic Optimal Control and Stochastic Optimization Probabilistische Nebenbedingungen in stochastich optimaler Regelung und stochastischer Optimierung Master-Thesis von Onur Celik Dezember 2018 Chance Constraints for Stochastic Optimal Control and Stochastic Optimization Pr

Jan Peters, 2018 .

Sim2Real in Robotics and Automation: Applications and Challenges

Kostas E. Bekris, C. Karen Liu, Dieter Fox, 2021, IEEE Trans Autom. Sci. Eng..

Special issue on "Bio-inspired computing for autonomous vehicles"

Yang Gao, Antonios Tsourdos, Jan Peters, 2012, Int. J. Intell. Comput. Cybern..

Learning to Control in Operational Space Learning to Control in Operational Space

Jan Peters, 2008 .

Learning Throwing and Catching Skills : Video Track

Jan Peters, Katharina Muelling, Jens Kober, 2012 .

Reinforcement Learning by Relative Entropy Policy Search

Yasemin Altun, Jan Peters, Katharina Mülling, 2010 .

Reinforcement learning in robotics: A survey

Jan Peters, Jens Kober, Jan Peters, 2013, Int. J. Robotics Res..

Reward-based decision making in pathological gambling: The roles of risk and delay

Jan Peters, A. Wiehler, 2015, Neuroscience Research.

Reinforcement Learning of Perceptual Coupling for Motor Primitives

Jan Peters, Jens Kober, Jan Peters, 2008, EWRL 2008.

Report from Dagstuhl Seminar 15411 Multimodal Manipulation Under Uncertainty

Jan Peters, S. Srinivasa, Robert W. Platt, 2016 .

Probabilistic Modeling of Human Dynamics for Intention Inference

Bernhard Schölkopf, Jan Peters, Zhikun Wang, 2012, Robotics: Science and Systems Conference.

Evolutionary training and abstraction yields algorithmic generalization of neural computers

Jan Peters, Elmar Rueckert, Daniel Tanneberg, 2020, Nature Machine Intelligence.

Imitation and Reinforcement Learning: Practical Algorithms for Motor Primitives in Robotics

Jan Peters, Jens Kober, Jan Peters, 2010 .

Modeling Robustness for Multi-Objective Optimization

Jan Peters, 2016 .

Seminar in Artificial Intelligence

Yasemin Altun, Jan Peters, Katharina Mülling, 2015 .

Reinforcement Learning for Humanoid Robots - Policy Gradients and Beyond

Jan Peters, S. Vijayakumar, S. Schaal, 2004 .

Reward Weighted Regression with Sample Reuse

Masashi Sugiyama, Jan Peters, Hirotaka Hachiya, 2011 .

Learning as a key ability for Human-Friendly Robots

Moritz Grosse-Wentrup, Jan Peters, Katharina Mülling, 2010 .

From Motor Learning to Interaction Learning in Robots

Olivier Sigaud, Jan Peters, Jan Peters, 2010, From Motor Learning to Interaction Learning in Robots.

A real-time model of the human knee for application in virtual orthopaedic trainer

Jan Peters, Jan Peters, 2000 .

Skill Learning for Robotics

Jan Peters, Jan Peters, 2010 .

Benchmarking of Policy Gradient Methods

Jan Peters, Jan Peters, 2007 .

Policy Learning for Robotics

Jan Peters, Jan Peters, 2007 .

Designing inclusion into engineering education : A fresh, practical look at how diversity impacts on engineering and strategies for change

Jan Peters, Carmen Leicht-Scholten, Anna Bouffier, 2018 .

Machine Learning for Robotics: Learning Methods for Robot Motor Skills

Jan Peters, Jan Peters, 2013 .

Learning to Pour Using Warped Features

Jan Peters, Oliver Kroemer, Sascha Brandl, 2014 .

Robot Learning

Stefan Schaal, Daniel D. Lee, Jan Peters, 2017, Encyclopedia of Machine Learning and Data Mining.

Scientific Societies Integrating Gender and Ethnoracial Diversity Efforts: A First Meeting Report from Amplifying the Alliance to Catalyze Change for Equity in STEM Success (ACCESS+)

Verónica A. Segarra, Jan Peters, L. Hill, 2022, Journal of Microbiology & Biology Education.

Reinforcement Learning to Adjust Robot Movements to New Situations

Jan Peters, Jens Kober, Erhan Öztop, 2010, IJCAI.

A Unifying Methodology for Robot Control with Redundant DOFs

Jun Nakanishi, Stefan Schaal, Jan Peters, 2008 .

Robotics Challenges for Machine Learning

Jan Peters, Marc Toussaint, Jan Peters, 2007, NIPS 2007.

Machine Learning for Robotics

Jan Peters, Jan Peters, 2013 .

Reinforcement learning for optimal control of arm movements

Jan Peters, Stefan Schaal, Evangelos Theodorou, 2007 .

Proceedings of the 6th International Cognitive Robotics Workshop (CogRob 2008)

Gerhard Lakemeyer, Jan Peters, Y. Lesperance, 2008 .

Neural Networks in Robot Control

Jan Peters, Jan Peters, 2000 .

Cyclist exposure to UFP and BC on urban routes in Antwerp, Belgium

Bernard De Baets, Jan Peters, Martine Van Poppel, 2014 .

Energy-optimal collision-free catching of flying targets with nonlinear optimization and learning

Jan Peters, Duy Nguyen-Tuong, Claudio Castellini, 2011 .

Recurrent neural networks from learning attractor dynamics

Stefan Schaal, Jan Peters, Jan Peters, 2003, NIPS 2003.

Algorithmen zum Automatischen Erlernen von Motorfähigkeiten (Policy Learning Algorithms for Motor Skills)

Jan Peters, Jens Kober, Stefan Schaal, 2010, at - Automatisierungstechnik.

Scaling Reinforcement Learning Paradigms for Motor Learning

Sethu Vijayakumar, Jan Peters, Stefan Schaal, 2003 .

Reinforcement Learning for Robotics

Jan Peters, Jan Peters, 2008, EWRL 2008.

Graph-Based Model Predictive Visual Imitation Learning

Jan Peters, 2022 .

Revisiting Grasp Map Representation with a Focus on Orientation in Grasp Synthesis

Jan Peters, P. Maragos, G. Chalvatzaki, 2020 .

Robot Learning of Mobile Manipulation With Reachability Behavior Priors

Jan Peters, G. Chalvatzaki, Snehal Jauhri, 2022, IEEE Robotics and Automation Letters.

Controlling the Cascade: Kinematic Planning for N-ball Toss Juggling

Jan Peters, Kai Ploeger, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Motor response vigour and visual fixation patterns reflect subjective valuation during intertemporal choice

Jan Peters, E. Smith, 2022, PLoS Comput. Biol..

Deterministic Variational Inference for Neural SDEs

Jan Peters, M. Kandemir, A. Look, 2021 .

Erotic cue exposure increases physiological arousal, biases choices towards immediate rewards and attenuates model-based reinforcement learning

Jan Peters, D. Mathar, K. Knauth, 2022, bioRxiv.

Deterministic Variational Inference for Neural SDEs

Jan Peters, M. Kandemir, A. Look, 2021 .

Reliable Real Time Ball Tracking for Robot Table Tennis

Jan Peters, B. Schölkopf, S. Gómez-González, 2019, Robotics.

Reinforcement Learning of Motor Skills in Robotics

Jan Peters, 2009 .

Autonomous Learning of Page Flipping Movements via Tactile Feedback

Jan Peters, Filipe Veiga, V. Santos, 2022, IEEE Transactions on Robotics.

Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes

Jan Peters, J. Watson, Joe Watson, 2022, CoRL.

Hierarchical Policy Blending as Inference for Reactive Robot Control

Jan Peters, Julen Urain, G. Chalvatzaki, 2022, ArXiv.

SE(3)-DiffusionFields: Learning cost functions for joint grasp and motion optimization through diffusion

Jan Peters, Julen Urain, G. Chalvatzaki, 2022 .

SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion

Jan Peters, Julen Urain, G. Chalvatzaki, 2022, 2209.03855.

Refining a DEI Assessment Tool for Use in Optimizing Professional STEM Societies for Gender Equity

Verónica A. Segarra, Jan Peters, H. Metcalf, 2022, Frontiers in Sociology.

Dopamine regulates decision thresholds in human reinforcement learning

Jan Peters, Ben Wagner, T. Sommer, 2022, bioRxiv.

MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction

Jan Peters, Dorothea Koert, V. Prasad, 2022, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).

Model-Based Reinforcement Learning for Stochastic Hybrid Systems

Jan Peters, Hany Abdulsamad, 2021, arXiv.org.

Adapting Object-Centric Probabilistic Movement Primitives with Residual Reinforcement Learning

Jan Peters, Dorothea Koert, João Carvalho, 2022, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).

Active Exploration for Robotic Manipulation

Devesh K. Jha, Jan Peters, B. Belousov, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Appetitive cue exposure increases neural reward responses without modulating temporal discounting

Jan Peters, M. Tittgemeyer, B. Kuzmanovic, 2022, bioRxiv.

How Crucial is Transformer in Decision Transformer?

Jan Peters, B. Belousov, Junning Huang, 2022, ArXiv.

Reinforcement learning to adjust parametrized motor primitives to new situations

Jan Peters, J. Kober, E. Oztop, 2012, Autonomous Robots.

Using probabilistic movement primitives in robotics

Jan Peters, G. Neumann, Christian Daniel, 2017, Autonomous Robots.

Conditioned Score-Based Models for Learning Collision-Free Trajectory Generation

Jan Peters, Julen Urain, João Carvalho, 2022 .

Active reward learning with a novel acquisition function

Jan Peters, Christian Daniel, Oliver Kroemer, 2015, Autonomous Robots.

Hierarchical Policy Blending As Optimal Transport

An T. Le, Jan Peters, G. Chalvatzaki, 2022, ArXiv.

A Win-Win Local Energy Market for Participants, Retailers, and the Network Operator : A Peer-to-Peer Trading-driven Case Study

M. I. Azim, Jan Peters, Liaqat Ali, 2022, 2022 IEEE 20th International Conference on Industrial Informatics (INDIN).

Integrated Bi-Manual Motion Generation and Control shaped for Probabilistic Movement Primitives

Luis F. C. Figueredo, Jan Peters, S. Haddadin, 2022, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).

Probabilistic movement primitives for coordination of multiple human–robot collaborative tasks

Jan Peters, G. Neumann, Oliver Kroemer, 2016, Autonomous Robots.

Learning Stable Vector Fields on Lie Groups

Jan Peters, Julen Urain, Davide Tateo, 2021, IEEE Robotics and Automation Letters.

Multi-Modal Learning for Dynamic Tactile Sensing

Christoph H. Lampert, Jan Peters, Oliver Kroemer, 2012 .

Towards net zero CO2 in 2050: an emission reduction pathway for organic soils in Germany

Jan Peters, J. Couwenberg, H. Joosten, 2021 .

Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery

Jan Peters, G. Chalvatzaki, Niklas Funk, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

The catecholamine precursor Tyrosine reduces autonomic arousal and decreases decision thresholds in reinforcement learning and temporal discounting

Jan Peters, D. Mathar, Deniz Tuzsus, 2022, PLoS Comput. Biol..

Regularized Deep Signed Distance Fields for Reactive Motion Generation

Jan Peters, Davide Tateo, G. Chalvatzaki, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Building Skill Learning Systems for Robotics

Kim D. Listmann, Jan Peters, M. Lutter, 2021, 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE).

Interaction primitives for human-robot cooperation tasks

Oliver Kroemer, Jan Peters, Heni Ben Amor, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Learning responsive robot behavior by imitation

Jan Peters, Heni Ben Amor, David Vogt, 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Finding the way forward: COVID-19 vaccination progress in Germany, Austria and Switzerland

Jan Peters, F. Paolucci, L. Kauer, 2021, Health Policy and Technology.

Robust Value Iteration for Continuous Control Tasks pdf

Shie Mannor, Dieter Fox, Jan Peters, 2021, Robotics: Science and Systems.

Value Iteration in Continuous Actions, States and Time

Shie Mannor, Dieter Fox, Jan Peters, 2021, ICML.

Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning

Junichiro Yoshimoto, Jan Peters, Kenji Doya, 2010, Neural Computation.

Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery

Bernhard Schölkopf, Moritz Grosse-Wentrup, Jan Peters, 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks

Jan Peters, Filipe Veiga, Riad Akrour, 2020, Frontiers in Robotics and AI.

Grip Stabilization of Novel Objects Using Slip Prediction

Jan Peters, Filipe Veiga, Tucker Hermans, 2018, IEEE Transactions on Haptics.

Dimensionality Reduction of Movement Primitives in Parameter Space pdf

Jan Peters, Samuele Tosatto, Jonas Stadtmueller, 2020, ArXiv.

Context-driven movement primitive adaptation

Jan Peters, Rudolf Lioutikov, Daniel Wilbers, 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

Incremental imitation learning of context-dependent motor skills

Jan Peters, Josef Wiemeyer, Guilherme Maeda, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Demonstration based trajectory optimization for generalizable robot motions

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Anticipative Interaction Primitives for Human-Robot Collaboration

Jan Peters, Guilherme Maeda, Marco Ewerton, 2016, AAAI Fall Symposia.

Learning interaction for collaborative tasks with probabilistic movement primitives

Jan Peters, Guilherme Maeda, Heni Ben Amor, 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

Autonomous reinforcement learning with hierarchical REPS

Jan Peters, Christian Daniel, Gerhard Neumann, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Structured Apprenticeship Learning

Oliver Kroemer, Jan Peters, Abdeslam Boularias, 2012, ECML/PKDD.

Learning Continuous Grasp Affordances by Sensorimotor Exploration

Oliver Kroemer, Justus H. Piater, Norbert Krüger, 2010, From Motor Learning to Interaction Learning in Robots.

A lightweight robotic arm with pneumatic muscles for robot learning

Jan Peters, Dieter Buchler, Heiko Ott, 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

Extended Tree Search for Robot Task and Motion Planning

Jan Peters, G. Chalvatzaki, Tianyu Ren, 2021, 2103.05456.

Multi-task policy search for robotics

Peter Englert, Dieter Fox, Jan Peters, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Data-Efficient Generalization of Robot Skills with Contextual Policy Search

Jan Peters, Gerhard Neumann, Marc Peter Deisenroth, 2013, AAAI.

Robot Learning From Randomized Simulations: A Review pdf

Jan Peters, Greg Turk, Wenhao Yu, 2021, Frontiers in Robotics and AI.

Generalizing pouring actions between objects using warped parameters

Oliver Kroemer, Jan Peters, Sascha Brandi, 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

The Power of Nature‐Based Solutions: How Peatlands Can Help Us to Achieve Key EU Sustainability Objectives

Niall Ó Brolcháin, Jan Peters, F. Tanneberger, 2020, Advanced Sustainable Systems.

A Nonparametric Off-Policy Policy Gradient

Jan Peters, Hany Abdulsamad, Samuele Tosatto, 2020, AISTATS.

Self-Paced Contextual Reinforcement Learning pdf

Jan Peters, Hany Abdulsamad, Boris Belousov, 2019, CoRL.

Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller

Luís Paulo Reis, Nuno Lau, Jan Peters, 2016, J. Intell. Robotic Syst..

Assisting Movement Training and Execution With Visual and Haptic Feedback

Jan Peters, Josef Wiemeyer, Guilherme Maeda, 2018, Front. Neurorobot..

Trial-wise exposure to visual appetitive cues increases physiological arousal but not temporal discounting

Jan Peters, K. Knauth, Kilian Knauth, 2021, bioRxiv.

Learning attribute grammars for movement primitive sequencing

Jan Peters, Guilherme Maeda, Filipe Veiga, 2019, Int. J. Robotics Res..

Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives

Kristian Kersting, Jan Peters, Guilherme Maeda, 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

Inducing Probabilistic Context-Free Grammars for the Sequencing of Robot Movement Primitives

Kristian Kersting, Jan Peters, Guilherme Maeda, 2018 .

Learning Coupled Forward-Inverse Models with Combined Prediction Errors

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

Learning probabilistic discriminative models of grasp affordances under limited supervision

Oliver Kroemer, Justus H. Piater, Yasemin Altun, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Efficient and Reactive Planning for High Speed Robot Air Hockey

Haitham Bou-Ammar, Jan Peters, Davide Tateo, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning pdf

Zhitang Chen, Haitham Bou-Ammar, Jan Peters, 2021, ArXiv.

Active reward learning with a novel acquisition function

Oliver Kroemer, Jan Peters, Christian Daniel, 2015, Auton. Robots.

An Experimental Evaluation of Bayesian Optimization on Bipedal Locomotion

Jan Peters, Marc Peter Deisenroth, Andre Seyfarth, 2014, ICRA 2014.

HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints

Kim D. Listmann, Jan Peters, M. Lutter, 2019, CoRL.

Data-Efficient Domain Randomization With Bayesian Optimization

Jan Peters, Michael Gienger, Fabio Muratore, 2020, IEEE Robotics and Automation Letters.

2008 Special Issue: Reinforcement learning of motor skills with policy gradients

Stefan Schaal, Jan Peters, Jan Peters, 2008 .

Europe's Covid-19 outliers: German, Austrian and Swiss policy responses during the early stages of the 2020 pandemic

Jan Peters, L. Kauer, M. Falkenbach, 2020, Health Policy and Technology.

Batch Reinforcement Learning With a Nonparametric Off-Policy Policy Gradient

Jan Peters, Samuele Tosatto, João Carvalho, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Nonparametric Offpolicy Policy Gradient pdf

Jan Peters, Hany Abdulsamad, Samuele Tosatto, 2020, ArXiv.

Local Energy Markets Improve Investment Returns of Residential BESS by Arbitrage Opportunities

M. I. Azim, Jan Peters, E. Pashajavid, 2022, 2022 IEEE Sustainable Power and Energy Conference (iSPEC).

Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems

Kim D. Listmann, Jan Peters, Michael Lutter, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments

Oliver Kroemer, Jan Peters, Herke van Hoof, 2014, IEEE Transactions on Robotics.

Model Predictive Control with Gaussian-Process-Supported Dynamical Constraints for Autonomous Vehicles

Jan Peters, R. Findeisen, Maik Pfefferkorn, 2023, ArXiv.

SN 1991bg - A type Ia supernova with a difference

Jan Peters, George Sonneborn, Robert P. Kirshner, 1993 .

High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards pdf

Jan Peters, Michael Lutter, Kai Ploeger, 2020, CoRL.

Imitation and Reinforcement Learning

Jan Peters, Jens Kober, Jan Peters, 2010, IEEE Robotics & Automation Magazine.

SKID RAW: Skill Discovery From Raw Trajectories

Jan Peters, Kai Ploeger, Elmar Rueckert, 2021, IEEE Robotics and Automation Letters.

Learning movement primitive libraries through probabilistic segmentation

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2017, Int. J. Robotics Res..

Probabilistic segmentation applied to an assembly task

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk

Jan Peters, Joe Watson, Jan Peters, 2021, 2021 American Control Conference (ACC).

Layered direct policy search for learning hierarchical skills

Jan Peters, Gerhard Neumann, Riad Akrour, 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

Combining physics and deep learning to learn continuous-time dynamics models

Jan Peters, M. Lutter, 2021, Int. J. Robotics Res..

Metric-Based Imitation Learning Between Two Dissimilar Anthropomorphic Robotic Arms pdf

Jan Peters, Armin Biess, Binyamin Manela, 2020, ArXiv.

Probabilistic movement primitives under unknown system dynamics

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2018, Adv. Robotics.

Model-free Probabilistic Movement Primitives for physical interaction

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Learning to Unscrew a Light Bulb from Demonstrations

Jan Peters, Jens Kober, Michael Gienger, 2014, ISR 2014.

Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning

Jan Peters, Simone Parisi, J. Pajarinen, 2019, Algorithms.

Active Incremental Learning of Robot Movement Primitives

Jan Peters, Guilherme Maeda, Takayuki Osa, 2017, CoRL.

Empowered skills

Jan Peters, Gerhard Neumann, Alexander Gabriel, 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

Alignment-based transfer learning for robot models

Jan Peters, Lehel Csató, Botond Attila Bócsi, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Multi-Task Policy Search pdf

Peter Englert, Dieter Fox, Jan Peters, 2013, ArXiv.

Manifold Gaussian Processes for regression

Carl E. Rasmussen, Jan Peters, Marc Peter Deisenroth, 2014, 2016 International Joint Conference on Neural Networks (IJCNN).

Non-parametric Policy Search with Limited Information Loss

Jan Peters, Herke van Hoof, Gerhard Neumann, 2017, J. Mach. Learn. Res..

Generalized exploration in policy search

Jan Peters, Herke van Hoof, Daniel Tanneberg, 2017, Machine Learning.

Model-Based Reinforcement Learning with Continuous States and Actions

Carl E. Rasmussen, Jan Peters, Marc Peter Deisenroth, 2008, ESANN.

Approximate dynamic programming with Gaussian processes

J. Peters, C.E. Rasmussen, M.P. Deisenroth, 2008, 2008 American Control Conference.

Robot Learning of Mobile Manipulation With Reachability Behavior Priors

Jan Peters, G. Chalvatzaki, Snehal Jauhri, 2022, IEEE Robotics and Automation Letters.

Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction

Jan Peters, Davide Tateo, G. Chalvatzaki, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

Probabilistic Approach to Physical Object Disentangling

Jan Peters, Gerhard Neumann, Joni Pajarinen, 2020, IEEE Robotics and Automation Letters.

Utilizing Human Feedback in POMDP Execution and Specification

Jan Peters, Joni Pajarinen, Janine Hoelscher, 2018, 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids).

A Hierarchical Approach to Active Pose Estimation

Jan Peters, Julen Urain, João Carvalho, 2022, ArXiv.

Reinforcement Learning using Guided Observability pdf

Jan Peters, Joni Pajarinen, Pascal Klink, 2021, ArXiv.

Solving Nonlinear Continuous State-Action-Observation POMDPs for Mechanical Systems with Gaussian Noise

Jan Peters, Marc Peter Deisenroth, Jan Peters, 2012, EWRL 2012.

Learning visual representations for perception-action systems

Oliver Kroemer, Justus H. Piater, Dirk Kraft, 2011, Int. J. Robotics Res..

Episodic Reinforcement Learning by Logistic Reward-Weighted Regression

Tom Schaul, Jürgen Schmidhuber, Jan Peters, 2008, ICANN.

Deep reinforcement learning under uncertainty for autonomous driving Deep Reinforcement Learning

Jan Peters, J. Pajarinen, H. Koeppl, 2022 .

Assessing Transferability From Simulation to Reality for Reinforcement Learning

Jan Peters, Michael Gienger, Fabio Muratore, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Learning to predict phases of manipulation tasks as hidden states

Oliver Kroemer, Jan Peters, Herke van Hoof, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Movement extraction by detecting dynamics switches and repetitions

Jan Peters, Silvia Chiappa, Jan Peters, 2010, NIPS.

Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning pdf

Jan Peters, Michael Lutter, Joe Watson, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

A Differentiable Newton Euler Algorithm for Multi-body Model Learning pdf

Jan Peters, Michael Lutter, Joe Watson, 2020, ArXiv.

Learning inverse dynamics models in O(n) time with LSTM networks

Jan Peters, Elmar Rueckert, Samuele Tosatto, 2017, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids).

Using model knowledge for learning inverse dynamics

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2010, 2010 IEEE International Conference on Robotics and Automation.

Computed torque control with nonparametric regression models

Duy Nguyen-Tuong, J. Peters, M. Seeger, 2008, 2008 American Control Conference.

Assessment and Spatial Planning for Peatland Conservation and Restoration: Europe’s Trans-Border Neman River Basin as a Case Study

Jan Peters, P. Angelstam, Michael Manton, 2021, Land.

The Inclusive Professional Framework for Societies: Changing Mental Models to Promote Diverse, Equitable, and Inclusive STEM Systems Change

Verónica A. Segarra, Jan Peters, H. Metcalf, 2022, Frontiers in Sociology.

A single dose of the catecholamine precursor Tyrosine reduces physiological arousal and decreases decision thresholds in reinforcement learning and temporal discounting

Jan Peters, D. Mathar, Tobias Marrenbach, 2022, bioRxiv.

A probabilistic approach to robot trajectory generation

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2013, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).

Online Kernel-Based Learning for Task-Space Tracking Robot Control

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2012, IEEE Transactions on Neural Networks and Learning Systems.

Using reward-weighted imitation for robot Reinforcement Learning

Jan Peters, Jens Kober, Jan Peters, 2009, 2009 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning.

Robot Reinforcement Learning on the Constraint Manifold

Haitham Bou-Ammar, Jan Peters, Davide Tateo, 2021, CoRL.

09341 Abstracts Collection - Cognition, Control and Learning for Robot Manipulation in Human Environments

Oliver Brock, Gordon Cheng, Michael Beetz, 2009, Cognition, Control and Learning for Robot Manipulation in Human Environments.

Multi-Channel Interactive Reinforcement Learning for Sequential Tasks.

Jan Peters, Dorothea Koert, Carlo D'Eramo, 2020 .

Multi-Channel Interactive Reinforcement Learning for Sequential Tasks

Jan Peters, Carlo D'Eramo, Dorothea Koert, 2020, Frontiers in Robotics and AI.

Gambling Environment Exposure Increases Temporal Discounting but Improves Model-Based Control in Regular Slot-Machine Gamblers

Jan Peters, Ben Wagner, D. Mathar, 2021, bioRxiv.

Convex optimization with an interpolation-based projection and its application to deep learning pdf

Asma Atamna, Jan Peters, Riad Akrour, 2020, Machine Learning.

Deep Optimal Control: Using the Euler-Lagrange Equation to learn an Optimal Feedback Control Law

Jan Peters, M. Lutter, 2019 .

Stability of Controllers for Gaussian Process Dynamics

Jan Peters, Duy Nguyen-Tuong, Bastian Bischoff, 2017, J. Mach. Learn. Res..

Learning multiple collaborative tasks with a mixture of Interaction Primitives

Jan Peters, Guilherme Maeda, Heni Ben Amor, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

Incremental online sparsification for model learning in real-time robot control

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2011, Neurocomputing.

Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills

Jan Peters, Georgia Chalvatzaki, Samuele Tosatto, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Opportunistic mobile air pollution monitoring: A case study with city wardens in Antwerp

Dick Botteldooren, Jan Peters, Bart Elen, 2016, Atmospheric Environment.

Algorithmen zum Automatischen Erlernen von Motorfähigkeiten

Stefan Schaal, Jan Peters, Jens Kober, 2010 .

Policy Learning - A Unified Perspective with Applications in Robotics

Jan Peters, Jens Kober, Duy Nguyen-Tuong, 2008, EWRL.

Towards Machine Learning of Motor Skills

Bernhard Schölkopf, Stefan Schaal, Jan Peters, 2007, AMS.

Policy Learning for Motor Skills

Stefan Schaal, Jan Peters, Jan Peters, 2007, ICONIP.

Incidental reinstatement of faces and scenes in medial temporal lobe subregions during word recognition

Jan Peters, H. Schultz, T. Sommer, 2021, bioRxiv.

Can Modular Finger Control for In-Hand Object Stabilization be accomplished by Independent Tactile Feedback Control Laws? pdf

Jan Peters, Filipe Veiga, Jan Peters, 2016, ArXiv.

SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion

Jan Peters, Julen Urain, G. Chalvatzaki, 2022, ArXiv.

A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors

Yaodong Yang, Jan Peters, Yali Du, 2023, ArXiv.

Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation

Siddhartha S. Srinivasa, Jan Peters, Tapomayukh Bhattacharjee, 2021, IEEE Robotics and Automation Letters.

Composable energy policies for reactive motion generation and reinforcement learning pdf

Anqi Li, Jan Peters, Carlo D'Eramo, 2021, Robotics: Science and Systems.

Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking

Jan Peters, G. Chalvatzaki, Tianyu Ren, 2022, ArXiv.

Extended Task and Motion Planning of Long-horizon Robot Manipulation

Jan Peters, G. Chalvatzaki, Tianyu Ren, 2021, ArXiv.

Learning Inverse Dynamics: a Comparison

Bernhard Schölkopf, Jan Peters, Duy Nguyen-Tuong, 2008, ESANN.

TD-regularized actor-critic methods

Jan Peters, M. E. Khan, Simone Parisi, 2018, Machine Learning.

A kernel-based approach to learning contact distributions for robot manipulation tasks

Jan Peters, Oliver Kroemer, Stefan Luettgen, 2017, Autonomous Robots.

Learning elementary movements jointly with a higher level task

Jan Peters, Jens Kober, Jan Peters, 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Acquiring and Generalizing the Embodiment Mapping From Human Observations to Robot Skills

Jan Peters, Guilherme Maeda, Dorothea Koert, 2016, IEEE Robotics and Automation Letters.

Blockchain-Based Local Energy Market Enabling P2P Trading: An Australian Collated Case Study on Energy Users, Retailers and Utilities

M. I. Azim, Jan Peters, S. Muyeen, 2022, IEEE Access.

Stable reinforcement learning with autoencoders for tactile and visual data

Jan Peters, Maximilian Karl, Patrick van der Smagt, 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Hierarchical Policy Blending As Optimal Transport

An T. Le, Jan Peters, G. Chalvatzaki, 2022, L4DC.

Increased temporal discounting and reduced model-based control in problem gambling are not substantially modulated by exposure to virtual gambling environments

Jan Peters, Ben Wagner, Luca R. Bruder, 2021 .

Learning robot grasping from 3-D images with Markov Random Fields

Oliver Kroemer, Jan Peters, Abdeslam Boularias, 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

GIS-gestützte Modellierung der Erreichbarkeiten ambulanter Pflegedienste nach SGB V und SGB XI in Unterfranken unter Berücksichtigung demographischer Entwicklungen

Jan Peters, S. Rauch, Jannis Burk, 2020 .

Adaptation and Robust Learning of Probabilistic Movement Primitives

Bernhard Schölkopf, Jan Peters, Gerhard Neumann, 2018, IEEE Transactions on Robotics.

Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components

Christoph H. Lampert, Jan Peters, Jan Peters, 2012, Journal of Real-Time Image Processing.

A High-Speed Object Tracker from Off-the-Shelf Components

Christoph H. Lampert, Jan Peters, Jan Peters, 2009, ICCV 2009.

Human-Robot Handshaking: A Review pdf

Jan Peters, Vignesh Prasad, Ruth Stock-Homburg, 2021, Int. J. Soc. Robotics.

Advances in Human-Robot Handshaking pdf

Jan Peters, Vignesh Prasad, Ruth Stock-Homburg, 2020, ICSR.

Learning strategies in table tennis using inverse reinforcement learning

Jan Peters, B. Schölkopf, Katharina Muelling, 2014, Biological Cybernetics.

A Differentiable Newton-Euler Algorithm for Real-World Robotics pdf

Jan Peters, Michael Lutter, Joe Watson, 2021, ArXiv.

Bayesian optimization for learning gaits under uncertainty

Jan Peters, M. Deisenroth, R. Calandra, 2016, Annals of Mathematics and Artificial Intelligence.

Learning Hierarchical Acquisition Functions for Bayesian Optimization

Jan Peters, Elmar Rueckert, J. Babič, 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Local Bayesian Optimization of Motor Skills

Jan Peters, Gerhard Neumann, Riad Akrour, 2017, ICML.

Robot Learning for Muscular Systems

Jan Peters, T. Asfour, 2020 .

Active Inference for Robotic Manipulation

Jan Peters, B. Belousov, Hany Abdulsamad, 2022, ArXiv.

Projections for Approximate Policy Iteration Algorithms

Jan Peters, Gerhard Neumann, Joni Pajarinen, 2019, ICML.

Policy Search with High-Dimensional Context Variables

Masashi Sugiyama, Voot Tangkaratt, Jan Peters, 2016, AAAI.

Information Gathering in Decentralized POMDPs by Policy Graph Improvement

Jan Peters, Joni Pajarinen, Mikko Lauri, 2019, AAMAS.

Active exploration for robot parameter selection in episodic reinforcement learning

Oliver Kroemer, Jan Peters, Jan Peters, 2011, 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).

Motor response vigour and fixations reflect subjective preferences during intertemporal choice

Jan Peters, Elke Smith, 2021 .

A kernel-based approach to learning contact distributions for robot manipulation tasks

Oliver Kroemer, Jan Peters, Simon Leischnig, 2018, Auton. Robots.

A comparison of contact distribution representations for learning to predict object interactions

Oliver Kroemer, Jan Peters, Simon Leischnig, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Set Size of Information in Long-Term Memory Similarly Modulates Retrieval Dynamics in Young and Older Adults

Jan Peters, N. Bunzeck, Tineke K Steiger, 2022, Frontiers in psychology.

Monte-Carlo Robot Path Planning

Jan Peters, J. Pajarinen, G. Chalvatzaki, 2022, IEEE Robotics and Automation Letters.

Residual Robot Learning for Object-Centric Probabilistic Movement Primitives

Jan Peters, Dorothea Koert, João Carvalho, 2022, ArXiv.

Learning Intention Aware Online Adaptation of Movement Primitives

Jan Peters, Susanne Trick, Dorothea Koert, 2019, IEEE Robotics and Automation Letters.

Guiding Trajectory Optimization by Demonstrated Distributions

Jan Peters, Gerhard Neumann, Rustam Stolkin, 2017, IEEE Robotics and Automation Letters.

Reinforcement Learning of Trajectory Distributions: Applications in Assisted Teleoperation and Motion Planning

Jan Peters, Masaki Takahashi, Guilherme Maeda, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Signatures of heuristic-based directed exploration in two-step sequential decision task behaviour

Jan Peters, D. Mathar, A. Brands, 2023, bioRxiv.

Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences

Jan Peters, Gerhard Neumann, Takayuki Osa, 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

A proportional power sharing method through a local control for a low-voltage islanded microgrid

M. I. Azim, M. H. Shawon, Jan Peters, 2022, Energy Reports.

A Local Energy Market Benefiting Power Grids and Energy Users: A P2P Trading-based Case Study

M. I. Azim, Jan Peters, Liaqat Ali, 2022, 2022 10th International Conference on Smart Grid (icSmartGrid).

Regularizing Reinforcement Learning with State Abstraction

Jan Peters, Gerhard Neumann, Filipe Veiga, 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

f-Divergence constrained policy improvement pdf

Jan Peters, Boris Belousov, Jan Peters, 2017, ArXiv.

Hierarchical Policy Blending as Inference for Reactive Robot Control

Jan Peters, Julen Urain, G. Chalvatzaki, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

Whether cycling around the city is in fact healthy in the light of air quality - Results of black carbon.

Jan Peters, J. Kamińska, J. Kazak, 2023, Journal of Environmental Management.

Experiments with Motor Primitives in Table Tennis

Jan Peters, Katharina Mülling, Jens Kober, 2010, ISER.

Identification and modelling of race driving styles

Jan Peters, Stefan Löckel, André Kretschi, 2021, Vehicle System Dynamics.

Evaluating Decision Transformer Architecture on Robot Learning Tasks Erklärung zur Abschlussarbeit gemäß §22 Abs. 7 und §23 Abs. 7 APB der TU Darmstadt Abbreviations, Symbols and Operators

Jan Peters, 2022 .

MushroomRL: Simplifying Reinforcement Learning Research pdf

Andrea Bonarini, Jan Peters, Marcello Restelli, 2020, J. Mach. Learn. Res..

Learning perceptual coupling for motor primitives

Betty J. Mohler, Jan Peters, Jens Kober, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Neural Linear Models with Functional Gaussian Process Priors

Jan Peters, Pascal Klink, Joe Watson, 2021 .

Patrick van der Smagt, Jan Peters, Philip Becker-Ehmck, 2019 .

Online optimal trajectory generation for robot table tennis

Jan Peters, Guilherme Maeda, Okan Koc, 2018, Robotics Auton. Syst..

Stochastic Optimal Control as Approximate Input Inference

Jan Peters, Hany Abdulsamad, Joe Watson, 2019, CoRL.

Learning to sequence movement primitives from demonstrations

Jan Peters, Jens Kober, Michael Gienger, 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

How P2P Trading Helps an Electricity Retailer Exposed to Volatile Spot Prices: A Case Study

M. I. Azim, Jan Peters, Arindam Ghosh, 2022, 2022 IEEE Sustainable Power and Energy Conference (iSPEC).

ReDSDF: Regularized Deep Signed Distance Fields for Robotics

Jan Peters, Davide Tateo, G. Chalvatzaki, 2022 .

SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion

Jan Peters, Julen Urain, G. Chalvatzaki, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

Efficient data reuse in value function approximation

Masashi Sugiyama, Jan Peters, Hirotaka Hachiya, 2009, 2009 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning.

Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation

Masashi Sugiyama, Jan Peters, Hirotaka Hachiya, 2007, AAAI.

Learning complex motions by sequencing simpler motion templates

Jan Peters, Wolfgang Maass, Gerhard Neumann, 2009, ICML '09.

Application of a Community Battery-Integrated Microgrid in a Blockchain-Based Local Energy Market Accommodating P2P Trading

Jan Peters, S. Muyeen, Liaqat Ali, 2023, IEEE Access.

PAC-Bayesian Analysis of Martingales and Multiarmed Bandits pdf

John Shawe-Taylor, François Laviolette, Jan Peters, 2011, ArXiv.

Parameter and model recovery of reinforcement learning models for restless bandit problems

Jan Peters, D. Mathar, E. Smith, 2021, bioRxiv.

Learning inverse dynamics models with contacts

Jan Peters, Serena Ivaldi, Marc Peter Deisenroth, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling

Heinz Koeppl, Abdelhak M. Zoubir, Jan Peters, 2018, J. Mach. Learn. Res..

Structured Output Gaussian Processes – Technical Report –

Jan Peters, B. Bócsi, 2012 .

Perception and prediction of the putting distance of robot putting movements under different visual/viewing conditions

Jan Peters, Marco Ewerton, Gerrit Kollegger, 2021, PloS one.

Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions pdf

Jan Peters, Hany Abdulsamad, Boris Belousov, 2021, ArXiv.

ArmSym: A Virtual Human–Robot Interaction Laboratory for Assistive Robotics

Jan Peters, M. Grosse-Wentrup, V. Jayaram, 2021, IEEE Transactions on Human-Machine Systems.

P2P Trading-enabled Local Energy Market Supplemented with Blockchain Technology: An Australian Case Study

M. I. Azim, Jan Peters, S. Muyeen, 2023, 2023 IEEE Green Technologies Conference (GreenTech).

Monitoring der Freiflächeninanspruchnahme und -versiegelung als Beitrag für eine nachhaltige Raumentwicklung in Bayern

Jan Peters, M. Thiel, H. Job, 2021, Raumforschung und Raumordnung | Spatial Research and Planning.

Exploration Driven by an Optimistic Bellman Equation

Jan Peters, Marcello Restelli, Carlo D'Eramo, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Learning Motor Skills - From Algorithms to Robot Experiments

Jan Peters, J. Kober, Jens Kober, 2013, Springer Tracts in Advanced Robotics.

Technical Report: “Exploration Driven by an Optimistic Bellman Equation”

Jan Peters, Marcello Restelli, J. Pajarinen, 2018 .

Learning Prioritized Control of Motor Primitives pdf

Jan Peters, Jens Kober, Jan Peters, 2012, ArXiv.

Learning table tennis with a Mixture of Motor Primitives

Jan Peters, Katharina Mülling, Jens Kober, 2010, 2010 10th IEEE-RAS International Conference on Humanoid Robots.

Relative Entropy Policy Search

Jan Peters, Y. Altun, Katharina Muelling, 2010, AAAI.

Machine Learning for Motor Skills in Robotics

Jan Peters, 2022 .

Model-Based Reinforcement Learning via Stochastic Hybrid Models

Jan Peters, Hany Abdulsamad, 2021, IEEE Open Journal of Control Systems.

Optimizing robot striking movement primitives with Iterative Learning Control

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Model-Based Reinforcement Learning for Stochastic Hybrid Systems pdf

Jan Peters, Hany Abdulsamad, Jan Peters, 2021, ArXiv.

Bayesian Domain Randomization for Sim-to-Real Transfer pdf

Jan Peters, Michael Gienger, Fabio Muratore, 2020, ArXiv.

Entropic Regularization of Markov Decision Processes

Jan Peters, Boris Belousov, Jan Peters, 2019, Entropy.

Learning Replanning Policies With Direct Policy Search

Jan Peters, Florian Brandherm, Gerhard Neumann, 2019, IEEE Robotics and Automation Letters.

Compatible natural gradient policy search

Jan Peters, Gerhard Neumann, Joni Pajarinen, 2019, Machine Learning.

TD-regularized actor-critic methods

Mohammad Emtiyaz Khan, Voot Tangkaratt, Jan Peters, 2018, Machine Learning.

Constraint-Space Projection Direct Policy Search

Jan Peters, Gerhard Neumann, Riad Akrour, 2018, EWRL 2018.

Hierarchical reinforcement learning of multiple grasping strategies with human instructions

Jan Peters, Gerhard Neumann, Takayuki Osa, 2018, Adv. Robotics.

Manifold-based multi-objective policy search with sample reuse

Jan Peters, Simone Parisi, Matteo Pirotta, 2017, Neurocomputing.

State-Regularized Policy Search for Linearized Dynamical Systems

Jan Peters, Hany Abdulsamad, Gerhard Neumann, 2017, ICAPS.

Model-Free Trajectory-based Policy Optimization with Monotonic Improvement

Jan Peters, Hany Abdulsamad, Gerhard Neumann, 2016, J. Mach. Learn. Res..

Generalizing Movements with Information-Theoretic Stochastic Optimal Control

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2014, J. Aerosp. Inf. Syst..

Sample-based informationl-theoretic stochastic optimal control

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Information-Theoretic Motor Skill Learning

Jan Peters, Gerhard Neumann, Marc Peter Deisenroth, 2013, AAAI 2013.

Minimax and entropic proximal policy optimization

Jan Peters, B. Belousov, Yunlong Song, 2018 .

Learning movement primitive attractor goals and sequential skills from kinesthetic demonstrations

Jan Peters, Jens Kober, Michael Gienger, 2015, Robotics Auton. Syst..

Learning Trajectory Distributions for Assisted Teleoperation and Path Planning

Jan Peters, Guilherme Maeda, Dorothea Koert, 2019, Front. Robot. AI.

An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients

Jan Peters, Davide Tateo, Fabio Muratore, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning

Aaron M. Dollar, Jan Peters, Carlo D'Eramo, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Assisted teleoperation in changing environments with a mixture of virtual guides

Jan Peters, Marco Ewerton, Oleg Arenz, 2020, Adv. Robotics.

Contextual Policy Search for Generalizing a Parameterized Biped Walking Controller

Luís Paulo Reis, Nuno Lau, Jan Peters, 2015, 2015 IEEE International Conference on Autonomous Robot Systems and Competitions.

Learning soft task priorities for control of redundant robots

Giuseppe Oriolo, Jan Peters, Serena Ivaldi, 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

Was ist eine Professur fuer Kuenstliche Intelligenz? pdf

Kristian Kersting, Jan Peters, Constantin A. Rothkopf, 2019, ArXiv.

Generalized Mean Estimation in Monte-Carlo Tree Search pdf

Jan Peters, Joni Pajarinen, Tuan Dam, 2019, IJCAI.

Deep spiking networks for model-based planning in humanoids

Jan Peters, Alexandros Paraschos, Daniel Tanneberg, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Latent space policy search for robotics

Jan Peters, Heni Ben Amor, Gerhard Neumann, 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Distributed Reinforcement Learning with Neural Networks for Robotics

Jan Peters, Elmar Rueckert, Tag der Einreichung, 2018 .

Dopamine regulates decision thresholds in human reinforcement learning in males.

Jan Peters, Ben Wagner, D. Mathar, 2023, Nature communications.

Learning to Categorize Bug Reports with LSTM Networks

Jan Peters, Elmar Rueckert, K. D. Gondaliya, 2018 .

Control of Musculoskeletal Systems Using Learned Dynamics Models

Bernhard Schölkopf, Jan Peters, Roberto Calandra, 2018, IEEE Robotics and Automation Letters.

Directed Acyclic Graph Neural Network for Human Motion Prediction

Yong Wang, Jan Peters, Georgia Chalvatzaki, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

The neural mechanisms of inter-temporal decision-making: understanding variability

Jan Peters, C. Büchel, 2011, Trends in Cognitive Sciences.

Large-Scale Web Scraping for Problem Gambling Research: A Case Study of COVID-19 Lockdown Effects in Germany

Jan Peters, Kai Kaspar, E. Smith, 2022, Journal of Gambling Studies.

Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning

Masashi Sugiyama, Jan Peters, Hirotaka Hachiya, 2011, Neural Computation.

Learning task-space tracking control with kernels

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Learning inverse kinematics with structured prediction

Bernhard Schölkopf, Jan Peters, Duy Nguyen-Tuong, 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Opportunistic mobile air quality mapping using sensors on postal service vehicles: from point clouds to actionable insights

Jan Peters, M. Van Poppel, J. Hofman, 2023, Frontiers in Environmental Health.

Prediction of Intention during Interaction with iCub with Probabilistic Movement Primitives

Jan Peters, A. Paraschos, F. Charpillet, 2017, Front. Robot. AI.

Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131)

Peter Dayan, Ales Leonardis, Jan Peters, 2011, Dagstuhl Reports.

Incremental Sparsification for Real-time Online Model Learning

Jan Peters, Duy Nguyen-Tuong, Jan Peters, 2010, AISTATS.

Learning Human-like Hand Reaching for Human-Robot Handshaking

Jan Peters, V. Prasad, R. Stock-Homburg, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Erotic cue exposure increases neural reward responses without modulating temporal discounting

Jan Peters, M. Tittgemeyer, B. Kuzmanovic, 2023, Imaging Neuroscience.

Active Inference or Control as Inference? A Unifying View pdf

Jan Peters, Joe Watson, Abraham Imohiosen, 2020, IWAI.

Trial-wise exposure to visual emotional cues increases physiological arousal but not temporal discounting.

Jan Peters, K. Knauth, 2022, Psychophysiology.

Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning

Jan Peters, Kai Ploeger, J. Pajarinen, 2023, ArXiv.

On the Benefit of Optimal Transport for Curriculum Reinforcement Learning

Jan Peters, J. Pajarinen, Carlo D'Eramo, 2023, ArXiv.

Differential Equations as a Model Prior for Deep Learning and its Applications in Robotics

Jan Peters, Michael Lutter, Jan Peters, 2020, ICLR 2020.

Chance-Constrained Trajectory Optimization for Non-linear Systems with Unknown Stochastic Dynamics

Jan Peters, Hany Abdulsamad, Onur Celik, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Optimizing the Execution of Dynamic Robot Movements With Learning Control

Jan Peters, Guilherme Maeda, Okan Koç, 2018, IEEE Transactions on Robotics.

Optimizing Execution of Dynamic Goal-Directed Robot Movements with Learning Control

Jan Peters, Guilherme J. Maeda, Okan Koç, 2018, ArXiv.

Nonlinear Model Predictive Control with Probabilistic Models

Jan Peters, M. Deisenroth, S. Ulbrich, 2013 .

Learning to Serve: An Experimental Study for a New Learning From Demonstrations Framework

Jan Peters, Okan Koç, Jan Peters, 2018, IEEE Robotics and Automation Letters.

Learning object-specific grasp affordance densities

N. Kruger, R. Detry, E. Baseski, 2009, 2009 IEEE 8th International Conference on Development and Learning.

Jointly learning trajectory generation and hitting point prediction in robot table tennis

Bernhard Schölkopf, Jan Peters, Yanlong Huang, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Learning motor skills from partially observed movements executed at different speeds

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Reinforcement learning of motor skills with policy gradients

Jan Peters, S. Schaal, 2008, Neural Networks.

Mixture of Attractors: A Novel Movement Primitive Representation for Learning Motor Skills From Demonstrations

Jan Peters, Jens Kober, Michael Gienger, 2018, IEEE Robotics and Automation Letters.

Generalized Multiple Correlation Coefficient as a Similarity Measurement between Trajectories

Jan Peters, Julen Urain, Jan Peters, 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

2010 Special Issue: Parameter-exploring policy gradients

J. Schmidhuber, Jan Peters, Thomas Rückstieß, 2010 .

Structured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems pdf

Jan Peters, Julen Urain, Davide Tateo, 2020, ArXiv.

Relative Entropy Inverse Reinforcement Learning

Jan Peters, J. Kober, Abdeslam Boularias, 2011, AISTATS.

Data-Efficient Generalization of Robot Skills with Contextual Policy Search

Jan Peters, M. Deisenroth, G. Neumann, 2013, AAAI.

Reinforcement Learning in Robotics

Jan Peters, 2014, Engineering International.

Practical Learning Algorithms for Motor Primitives in Robotics

Jan Peters, Jens Kober, Jan Peters, 2010 .

Real-Time Local GP Model Learning

Jan Peters, Duy Nguyen-Tuong, Matthias W. Seeger, 2010, From Motor Learning to Interaction Learning in Robots.

On the Analysis of Mathematical Practices in Signal Theory Courses

Jan Peters, R. Hochmuth, 2021, International Journal of Research in Undergraduate Mathematics Education.

Sampling-Free Probabilistic Deep State-Space Models

Jan Peters, M. Kandemir, Barbara Rakitsch, 2023, ArXiv.

Learning New Basic Movements for Robotics

Jan Peters, Jens Kober, Jan Peters, 2009, AMS.

Reinforcement learning of motor skills with policy gradients

Jan Peters, S. Schaal, 2008, Neural Networks.

Learning Robot Dynamics for Computed Torque Control Using Local Gaussian Processes Regression

Duy Nguyen-Tuong, J. Peters, Jan Peters, 2008, 2008 ECSIS Symposium on Learning and Adaptive Behaviors for Robotic Systems (LAB-RS).

A comparison of distance measures for learning nonparametric motor skill libraries

Jan Peters, Svenja Stark, Elmar Rueckert, 2017, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids).

Real Robot Challenge: A Robotics Competition in the Cloud

Charles B. Schaff, Harshit S. Sikchi, Matthew R. Walter, 2021, Neural Information Processing Systems.

Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks

Jan Peters, Haitham Bou-Ammar, Davide Tateo, 2023, IEEE Transactions on Robotics.

Scaling Reinforcement Learning Paradigms for Motor Control

Stefan Schaal, Sethu Vijayakumar, Jan Peters, 2003 .

Differentiable Implicit Layers pdf

Jan Peters, Melih Kandemir, Rainer Gemulla, 2020, ArXiv.

Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer

Jan Peters, Elmar Rueckert, Daniel Tanneberg, 2019, ArXiv.

Instrumente für klimaverträgliche Moorbodennutzung: Moorschutz in der Gemeinsamen Agrarpolitik

Jan Peters, Sabine Wichmann, Sophie Hirschelmann, 2020 .

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals

Jan Peters, Daniel Tanneberg, Elmar A. Rückert, 2017, CoRL.

Extended Task and Motion Planning of Long-horizon Robot Manipulation pdf

Jan Peters, Georgia Chalvatzaki, Tianyu Ren, 2021, ArXiv.

A Probabilistic Framework for Imitating Human Race Driver Behavior

Jan Peters, Stefan Löckel, Peter van Vliet, 2020, IEEE Robotics and Automation Letters.

Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning

Jan Peters, Masashi Sugiyama, Hirotaka Hachiya, 2011, Neural Computation.

Efficient Sample Reuse in EM-Based Policy Search

Masashi Sugiyama, Jan Peters, Hirotaka Hachiya, 2009, ECML/PKDD.