The majority of the publications can also be obtained by Google Scholar where incomplete lists of citations are also given.


submitted

  •     Bib
    Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen, J. (submitted). A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search, Submitted to the Journal of Machine Learning Research (JMLR).
  •       Bib
    Klink, P.; D`Eramo, C.; Peters, J.; Pajarinen, J. (submitted). On the Benefit of Optimal Transport for Curriculum Reinforcement Learning, Submitted to the IEEE Transaction on Pattern Analysis and Machine Intelligence (T-PAMI).
  •       Bib
    Klink, P.; Wolf, F.; Ploeger, K.; Peter, J.; Pajarinen, J. (submitted). Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning, Submitted to the IEEE Transactions on Robotics (T-RO).
  •     Bib
    Look, A.; Rakitsch, B.; Kandemir, M.; Peters, J. (submitted). Sampling-Free Probabilistic Deep State-Space Models, Submitted to Transactions on Pattern Analysis and Machine Intelligence (PAMI).
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    Lutter, M.; Silberbauer, J.; Watson, J.; Peters, J. (submitted). A Differentiable Newton-Euler Algorithm for Real-World Robotics, Submitted to the IEEE Transaction of Robotics (T-Ro).

in press

  •     Bib
    Abdulsamad, H.; Nickl, P.; Klink, P.; Peters, J. (in press). Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI).
  •   Bib
    Abdulsamad, H.; Peters, J. (in press). Model-Based Reinforcement Learning via Stochastic Hybrid Models, IEEE Open Journal of Control Systems, Special Section: Intersection of Machine Learning with Control.
  •     Bib
    Flynn, H.; Reeb, D.; Kandemir, M.; Peters, J. (in press). PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI).
  •   Bib
    Loeckel, S.; Ju, S.; Schaller, M.; van Vliet, P..; Peters, J. (in press). An Adaptive Human Driver Model for Realistic Race Car Simulations, IEEE Transactions on Systems, Man and Cybernetics: Systems.
  •   Bib
    Urain, J.; Li, A.; Liu, P.; D'Eramo, C.; Peters, J. (in press). Composable energy policies for reactive motion generation and reinforcement learning, International Journal of Robotics Research (IJRR).
  •     Bib
    Weng, Y.; Matsuda, T.; Sekimoria, Y.; Pajarinen, J.; Peters, J.; Maki, T. (in press). Establishment of Line-of-Sight Optical Links Between Autonomous Underwater Vehicles: Field Experiment and Performance Validation, Applied Ocean Research.

2023

  •       Bib
    Al-Hafez, F.; Tateo, D.; Arenz, O.; Zhao, G.; Peters, J. (2023). LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning, International Conference on Learning Representations (ICLR).
  •       Bib
    Al-Hafez, F.; Tateo, D.; Arenz, O.; Zhao, G.; Peters, J. (2023). Least Squares Inverse Q-Learning, European Workshop on Reinforcement Learning (EWRL).
  •     Bib
    Arenz, O.; Dahlinger, P.; Ye, Z.; Volpp, M.; Neumann, G. (2023). A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models, Transactions on Machine Learning Research (TMLR).
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    Bethge, J.; Pfefferkorn, M.; Rose, A.; Peters, J.; Findeisen, R. (2023). Model predictive control with Gaussian-process-supported dynamical constraints for autonomous vehicles, Proceedings of the 22nd World Congress of the International Federation of Automatic Control.
  •     Bib
    Bjelonic, F.; Lee, J.; Arm, P.; Sako, D.; Tateo, D.; Peters, J.; Hutter, M. (2023). Learning-Based Design and Control for Quadrupedal Robots With Parallel-Elastic Actuators, IEEE Robotics and Automation Letters (R-AL), 8, 3, pp.1611-1618.
  •     Bib
    Buechler, D.; Calandra, R.; Peters, J. (2023). Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots, Robotics and Autonomous Systems, 159, 104230.
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    Buechler, D.; Guist, S.; Calandra, R.; Berenz, V.; Schoelkopf, B.; Peters, J. (2023). Learning to Play Table Tennis From Scratch using Muscular Robots, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE T-TRo Track.
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    Carvalho, J.; Le, A.T.; Baierl, M.; Koert, D.; Peters, J. (2023). Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Flynn, H.; Reeb, D.; Kandemir, M.; Peters, J. (2023). Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
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    Funk, N.; Mueller, P.-O.; Belousov, B.; Savchenko, A.; Findeisen, R.; Peters, J. (2023). High-Resolution Pixelwise Contact Area and Normal Force Estimation for the GelSight Mini Visuotactile Sensor Using Neural Networks, Embracing Contacts-Workshop at ICRA 2023.
  •   Bib
    Gruner, T.; Belousov, B.; Muratore, F.; Palenicek, D.; Peters, J. (2023). Pseudo-Likelihood Inference, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •       Bib
    Hansel, K.; Urain, J.; Peters, J.; Chalvatzaki, G. (2023). Hierarchical Policy Blending as Inference for Reactive Robot Control, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
  •     Bib
    Ju, S.; van Vliet, P.; Arenz, O.; Peters, J. (2023). Digital Twin of a Driver-in-the-Loop Race Car Simulation with Contextual Reinforcement Learning, IEEE Robotics and Automation Letters (RA-L), 8, 7, pp.4107-4114.
  •       Bib
    Le, A. T.; Hansel, K.; Peters, J.; Chalvatzaki, G. (2023). Hierarchical Policy Blending As Optimal Transport, 5th Annual Learning for Dynamics & Control Conference (L4DC), PMLR.
  •       Bib
    Le, A.T.; Chalvatzaki, G.; Biess, A.; Peters, J. (2023). Accelerating Motion Planning via Optimal Transport, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •     Bib
    Le, A.T.; Chalvatzaki, G.; Biess, A.; Peters, J. (2023). Accelerating Motion Planning via Optimal Transport, IROS 2023 Workshop on Differentiable Probabilistic Robotics: Emerging Perspectives on Robot Learning.
  •       Bib
    Liu, P.; Zhang, K.; Tateo, D.; Jauhri, S.; Hu, Z.; Peters, J. Chalvatzaki, G. (2023). Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
  •     Bib
    Liu, Y.; Belousov, B.; Funk, N.; Chalvatzaki, G.; Peters, J.; Tessman, O. (2023). Auto(mated)nomous Assembly, International Conference on Trends on Construction in the Post-Digital Era, pp.167-181, Springer, Cham.
  •     Bib
    Look, A.; Kandemir, M.; Rakitsch, B.; Peters, J. (2023). A Deterministic Approximation to Neural SDEs, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 45, 4, pp.4023-4037.
  •     Bib
    Look, A.; Kandemir, M.; Rakitsch, B.; Peters, J. (2023). Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems, Transactions on Machine Learning Research (TMLR).
  •   Bib
    Luis, C.; Bottero, A.G.; Vinogradska, J.; Berkenkamp, F.; Peters, J. (2023). Model-Based Uncertainty in Value Functions, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
  •       Bib
    Lutter, M.; Belousov, B.; Mannor, S.; Fox, D.; Garg, A.; Peters, J. (2023). Continuous-Time Fitted Value Iteration for Robust Policies, IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI).
  •     Bib
    Lutter, M.; Peters, J. (2023). Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models, International Journal of Robotics Research (IJRR), 42, 3.
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    Palenicek, D.; Lutter, M.; Carvalho, J.; Peters, J. (2023). Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning, International Conference on Learning Representations (ICLR).
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    Peters, S.; Peters, J.; Findeisen, R. (2023). Quantifying Uncertainties along the Automated Driving Stack, ATZ worldwide volume, 125, pp.62-65.
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    Scherf, L.; Schmidt, A.; Pal, S.; Koert, D. (2023). Interactively learning behavior trees from imperfect human demonstrations, Frontiers in Robotics and AI, 10.
  •       Bib
    Urain, J.; Funk, N; Peters, J. ; Chalvatzaki G (2023). SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion, International Conference on Robotics and Automation (ICRA).
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    Urain, J.; Tateo, D.; Peters, J. (2023). Learning Stable Vector Fields on Lie Groups, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE R-AL Track.
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    Vincent, T.; Belousov, B.; D'Eramo, C.; Peters J. (2023). Iterated Deep Q-Network: Efficient Learning of Bellman Iterations for Deep Reinforcement Learning, European Workshop on Reinforcement Learning (EWRL).
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    Zelch, C.; Peters, J.; von Stryk, C. (2023). Start State Selection for Control Policy Learning from Optimal Trajectories, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Zhu, Y.; Nazirjonov, S.; Jiang, B.; Colan, J.; Aoyama, T.; Hasegawa, Y.; Belousov, B.; Hansel, K.; Peters, J. (2023). Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation, IEEE International Conference on Cyborg and Bionic Systems, pp.49-52.

2022

  •     Bib
    Akrour, R.; Tateo, D.; Peters, J. (2022). Continuous Action Reinforcement Learning from a Mixture of Interpretable Experts, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 44, 10, pp.6795-6806.
  •       Bib
    Belousov, B.; Wibranek, B.; Schneider, J.; Schneider, T.; Chalvatzaki, G.; Peters, J.; Tessmann, O. (2022). Robotic Architectural Assembly with Tactile Skills: Simulation and Optimization, Automation in Construction, 133, pp.104006.
  •     Bib
    Buechler, D.; Guist, S.; Calandra, R.; Berenz, V.; Schoelkopf, B.; Peters, J. (2022). Learning to Play Table Tennis From Scratch using Muscular Robots, IEEE Transactions on Robotics (T-Ro), 38, 6, pp.3850-3860.
  •     Bib
    Carvalho, J.; Baierl, M; Urain, J; Peters, J. (2022). Conditioned Score-Based Models for Learning Collision-Free Trajectory Generation, NeurIPS 2022 Workshop on Score-Based Methods.
  •     Bib
    Carvalho, J.; Koert, D.; Daniv, M.; Peters, J. (2022). Adapting Object-Centric Probabilistic Movement Primitives with Residual Reinforcement Learning, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
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    Carvalho, J.; Peters, J. (2022). An Analysis of Measure-Valued Derivatives for Policy Gradients, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Cowen-Rivers, A.; Lyu, W.; Tutunov, R.; Wang, Z.; Grosnit, A.; Griffiths, R.R.; Maraval, A.; Jianye, H.; Wang, J.; Peters, J.; Bou Ammar, H. (2022). HEBO: An Empirical Study of Assumptions in Bayesian Optimisation, Journal of Artificial Intelligence Research, 74, pp.1269-1349.
  •     Bib
    Cowen-Rivers, A.I.; Palenicek, D.; Moens, V.; Abdullah, M.A.; Sootla, A.; Wang, J.; Bou-Ammar, H. (2022). SAMBA: safe model-based & active reinforcement learning, Machine Learning.
  •     Bib
    Flynn, H.; Reeb, D.; Kandemir, M.; Peters, J. (2022). PAC-Bayesian Lifelong Learning For Multi-Armed Bandits, Data Mining and Knowledge Discovery, 36, 2, pp.841-876.
  •       Bib
    Funk, N.; Menzenbach, S.; Chalvatzaki, G.; Peters, J. (2022). Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Funk, N.; Schaff, C.; Madan, R.; Yoneda, T.; Urain, J.; Watson, J.; Gordon, E.; Widmaier, F; Bauer, S.; Srinivasa, S.; Bhattacharjee, T.; Walter, M.; Peters, J. (2022). Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation, IEEE Robotics and Automation Letters (R-AL).
  •     Bib
    Galljamov, R.; Zhao, G.; Belousov, B.; Seyfarth, A.; Peters, J. (2022). Improving Sample Efficiency of Deep Reinforcement Learning for Bipedal Walking, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
  •       Bib
    Hansel, K.; Moos, J.; Abdulsamad, H.; Stark, S.; Clever, D.; Peters, J. (2022). Robust Reinforcement Learning: A Review of Foundations and Recent Advances, Machine Learning and Knowledge Extraction, 4, 1, pp.276--315, MDPI.
  •     Bib
    Klink, P.; D`Eramo, C.; Peters, J.; Pajarinen, J. (2022). Boosted Curriculum Reinforcement Learning, International Conference on Learning Representations (ICLR).
  •     Bib
    Klink, P.; Yang, H.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2022). Curriculum Reinforcement Learning via Constrained Optimal Transport, International Conference on Machine Learning (ICML).
  •     Bib
    Liu, P.; Zhang, K.;Tateo D.; Jauhri S.; Peters J.; Chalvatzaki G.; (2022). Regularized Deep Signed Distance Fields for Reactive Motion Generation, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Loeckel, S.; Kretschi, A.; van Vliet, P.; Peters, J. (2022). Identification and modelling of race driving styles, Vehicle System Dynamics, 60, 8, pp.2890--2918.
  •     Bib
    Memmel, M.; Liu, P.; Tateo, D.; Peters, J. (2022). Dimensionality Reduction and Prioritized Exploration for Policy Search, 25th International Conference on Artificial Intelligence and Statistics (AISTATS).
  •       Bib
    Muratore, F.; Ramos, F.; Turk, G.; Yu, W.; Gienger, M.; Peters, J. (2022). Robot Learning from Randomized Simulations: A Review, Frontiers in Robotics and AI, 9.
  •     Bib
    Palenicek, D.; Lutter, M., Peters, J. (2022). Revisiting Model-based Value Expansion, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Parisi, S.; Tateo, D.; Hensel, M.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2022). Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning, Algorithms, 15, 3, pp.81.
  •     Bib
    Ploeger, K.; Peters, J. (2022). Controlling the Cascade: Kinematic Planning for N-ball Toss Juggling, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Prasad, V.; Koert, D.; Stock-Homburg, R.; Peters, J.; Chalvatzaki, G. (2022). MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction, IEEE-RAS International Conference on Humanoid Robots (Humanoids).
  •       Bib
    Prasad, V.; Stock-Homburg, R.; Peters, J. (2022). Human-Robot Handshaking: A Review, International Journal of Social Robotics (IJSR), 14, 1, pp.277-293.
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    Scherf, L.; Turan, C.; Koert, D. (2022). Learning from Unreliable Human Action Advice in Interactive Reinforcement Learning, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
  •       Bib
    Schneider, T.; Belousov, B.; Abdulsamad, H.; Peters, J. (2022). Active Inference for Robotic Manipulation, 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •       Bib
    Schneider, T.; Belousov, B.; Chalvatzaki, G.; Romeres, D.; Jha, D.K.; Peters, J. (2022). Active Exploration for Robotic Manipulation, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Siebenborn, M.; Belousov, B.; Huang, J.; Peters, J. (2022). How Crucial is Transformer in Decision Transformer?, Foundation Models for Decision Making Workshop at Neural Information Processing Systems.
  •     Bib
    Tosatto, S.; Carvalho, J.; Peters, J. (2022). Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 44, 10, pp.5996--6010.
  •       Bib
    Urain, J.; Le, A.T.; Lambert, A.; Chalvatzaki, G.; Boots, B.; Peters, J. (2022). Learning Implicit Priors for Motion Optimization, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Urain, J.; Tateo, D; Peters, J. (2022). Learning Stable Vector Fields on Lie Groups, Robotics and Automation Letters (RA-L).
  •     Bib
    Vorndamme, J.; Carvalho, J.; Laha, R.; Koert, D.; Figueredo, L.; Peters, J.; Haddadin, S. (2022). Integrated Bi-Manual Motion Generation and Control shaped for Probabilistic Movement Primitives, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
  •   Bib
    Watson, J.; Hanher, B.; Peters, J. (2022). Differentiable Simulators as Gaussian Processes, R:SS Workshop: Differentiable Simulation for Robotics.
  •     Bib
    Watson, J.; Peters, J. (2022). Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes, Conference on Robot Learning (CoRL).
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    Watson, J.; Peters, J.; (2022). Stationary Posterior Policy Iteration with Variational Inference, The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
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    Weng, Y.; Matsuda, T.; Sekimuri, Y.; Pajarinen, J.; Peters, J.; Maki, T. (2022). Pointing Error Control of Underwater Wireless Optical Communication on Mobile Platform, IEEE Photonics Technology Letters, 34, 13, pp.699-702.
  •     Bib
    Weng, Y.; Pajarinen, J.; Akrour, R.; Matsuda, T.; Peters, J.; Maki, T. (2022). Reinforcement Learning Based Underwater Wireless Optical Communication Alignment for Multiple Autonomous Underwater Vehicles, IEEE Journal of Oceanic Engineering, 47, 4, pp.1231-1245.
  •       Bib
    You, B.; Arenz, O.; Chen, Y.; Peters, J. (2022). Integrating Contrastive Learning with Dynamic Models for Reinforcement Learning from Images, Neurocomputing.
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    Zheng, Y.; Veiga, F.F.; Peters, J.; Santos, V.J. (2022). Autonomous Learning of Page Flipping Movements via Tactile Feedback, IEEE Transactions on Robotics (T-Ro), 38, 5, pp.2734 - 2749.
  •     Bib
    Zheng, Y.; Veiga, F.F.; Peters, J.; Santos, V.J. (2022). Autonomous Learning of Page Flipping Movements via Tactile Feedback, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

2021

  •     Bib
    Abdulsamad, H.; Dorau, T.; Belousov, B.; Zhu, J.-J; Peters, J. (2021). Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative Entropy Trust-Regions, arXiv.
  •     Bib
    Abdulsamad, H.; Nickl, P.; Klink, P.; Peters, J. (2021). A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Abdulsamad, H.; Peters, J. (2021). Model-Based Reinforcement Learning for Stochastic Hybrid Systems, arXiv.
  •     Bib
    Akrour, R.; Atamna, A.; Peters, J. (2021). Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning, Machine Learning (MACH), 110, 8, pp.2267-2289.
  •     Bib
    Belousov, B.; Abdulsamad H.; Klink, P.; Parisi, S.; Peters, J. (2021). Reinforcement Learning Algorithms: Analysis and Applications, Studies in Computational Intelligence, Springer International Publishing.
  •   Bib
    Bustamante, S.; Peters, J.; Schoelkopf, B.; Grosse-Wentrup, M.; Jayaram, V. (2021). ArmSym: a virtual human-robot interaction laboratory for assistive robotics, IEEE Transactions on Human-Machine Systems, 51, 6, pp.568-577.
  •     Bib
    Carvalho, J., Tateo, D., Muratore, F., Peters, J. (2021). An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients, International Joint Conference on Neural Networks (IJCNN).
  •     Bib
    Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen J. (2021). Convex Regularization in Monte-Carlo Tree Search, Proceedings of the International Conference on Machine Learning (ICML).
  •   Bib
    D`Eramo, C.; Cini, A.; Nuara, A.; Pirotta, M.; Alippi, C.; Peters, J.; Restelli, M. (2021). Gaussian Approximation for Bias Reduction in Q-Learning, Journal of Machine Learning Research (JMLR).
  •     Bib
    D`Eramo, C.; Davide, T; Bonarini, A.; Restelli, M.; Peters, J. (2021). MushroomRL: Simplifying Reinforcement Learning Research, Journal of Machine Learning Research (JMLR), 22, 131, pp.1-5.
  •       Bib
    Funk, N.; Baumann, D.; Berenz, V.; Trimpe, S. (2021). Learning event-triggered control from data through joint optimization, IFAC Journal of Systems and Control, 16, pp.100144.
  •       Bib
    Funk, N.; Chalvatzaki, G.; Belousov, B.; Peters, J. (2021). Learn2Assemble with Structured Representations and Search for Robotic Architectural Construction, Conference on Robot Learning (CoRL).
  •     Bib
    Hansel, K.; Moos, J.; Derstroff, C. (2021). Benchmarking the Natural Gradient in Policy Gradient Methods and Evolution Strategies, Reinforcement Learning Algorithms: Analysis and Applications, pp.69--84, Springer.
  •     Bib
    Hoefer, S.; Bekris, K.; Handa, A.; Gamboa, J.C.; Golemo, F.; Mozifian, M.; Atkeson, C.G., Fox, D.; Goldberg, K.; Leonard, J.; Liu, C.K.; Peters, J.; Song, S.; Welinder, P.; White, M. (2021). Sim2Real in Robotics and Automation: Applications and Challenges, IEEE Transactions on Automation Science (T-ASE), 18, 2, pp.398-400.
  •     Bib
    Klink, P.; Abdulsamad, H.; Belousov, B.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2021). A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning, Journal of Machine Learning Research (JMLR).
  •   Bib
    Knaust, M.; Koert, D. (2021). Guided Robot Skill Learning: A User-Study on Learning Probabilistic Movement Primitives with Non-Experts, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Lampariello, R.; Mishra, H.; Oumer, N.W.; Peters, J. (2021). Robust Motion Prediction of a Free-Tumbling Satellite with On-Ground Experimental Validation, Journal of Guidance, Control, and Dynamics, 44, 10, pp.1777-1793.
  •   Bib
    Li, Q.; Chalvatzaki, G.; Peters, J.; Wang, Y. (2021). Directed Acyclic Graph Neural Network for Human Motion Prediction, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Liu, P.; Tateo D.; Bou-Ammar, H.; Peters, J. (2021). Efficient and Reactive Planning for High Speed Robot Air Hockey, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Liu, P.; Tateo D.; Bou-Ammar, H.; Peters, J. (2021). Robot Reinforcement Learning on the Constraint Manifold, Proceedings of the Conference on Robot Learning (CoRL).
  •   Bib
    Lutter, M.; Clever, D.; Kirsten, R.; Listmann, K.; Peters, J. (2021). Building Skill Learning Systems for Robotics, Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE).
  •     Bib
    Lutter, M.; Mannor, S.; Peters, J.; Fox, D.; Garg, A. (2021). Value Iteration in Continuous Actions, States and Time, International Conference on Machine Learning (ICML).
  •     Bib
    Lutter, M.; Mannor, S.; Peters, J.; Fox, D.; Garg, A. (2021). Robust Value Iteration for Continuous Control Tasks, Robotics: Science and Systems (RSS).
  •     Bib
    Lutter, M.; Silberbauer, J.; Watson, J.; Peters, J. (2021). Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •   Bib
    Morgan, A.; Nandha, D.; Chalvatzaki, G.; D'Eramo, C.; Dollar, A.; Peters, J. (2021). Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Muratore, F.; Eilers, C.; Gienger, M.; Peters, J. (2021). Data-efficient Domain Randomization with Bayesian Optimization, IEEE Robotics and Automation Letters (RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), IEEE.
  •       Bib
    Muratore, F.; Gienger, M.; Peters, J. (2021). Assessing Transferability from Simulation to Reality for Reinforcement Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 43, 4, pp.1172-1183, IEEE.
  •     Bib
    Muratore, F.; Gruner, T.; Wiese, F.; Belousov, B.; Gienger, M.; Peters, J. (2021). Neural Posterior Domain Randomization, Conference on Robot Learning (CoRL).
  •     Bib
    Palenicek, D. (2021). A Survey on Constraining Policy Updates Using the KL Divergence, Reinforcement Learning Algorithms: Analysis and Applications, pp.49-57.
  •     Bib
    Prasad, V.; Stock-Homburg, R.; Peters, J. (2021). Learning Human-like Hand Reaching for Human-Robot Handshaking, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •   Bib
    Rawal, N.; Koert, D.; Turan, C.; Kersting, K.; Peters, J.; Stock-Homburg, R. (2021). ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition, Frontiers in Robotics & AI, 8, 730317.
  •     Bib
    Tanneberg, D.; Ploeger, K.; Rueckert, E.; Peters, J. (2021). SKID RAW: Skill Discovery from Raw Trajectories, IEEE Robotics and Automation Letters (RA-L).
  •       Bib
    Tosatto, S.; Akrour, R.; Peters, J. (2021). An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions, Stats, 4, pp.1--17.
  •   Bib
    Tosatto, S.; Chalvatzaki, G.; Peters, J. (2021). Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Urain, J.; Li, A.; Liu, P.; D'Eramo, C.; Peters, J. (2021). Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning, Robotics: Science and Systems (RSS).
  •     Bib
    Watson, J.; Lin J. A.; Klink, P.; Pajarinen, J.; Peters, J. (2021). Latent Derivative Bayesian Last Layer Networks, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
  •     Bib
    Watson, J.; Lin, J. A.; Klink, P.; Peters, J. (2021). Neural Linear Models with Functional Gaussian Process Priors, 3rd Symposium on Advances in Approximate Bayesian Inference (AABI).
  •     Bib
    Watson, J.; Peters, J. (2021). Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk, American Control Conference (ACC).
  •     Bib
    Wibranek, B.; Liu, Y.; Funk, N.; Belousov, B.; Peters, J.; Tessmann, O. (2021). Reinforcement Learning for Sequential Assembly of SL-Blocks: Self-Interlocking Combinatorial Design Based on Machine Learning, Proceedings of the 39th eCAADe Conference.

2020

  •     Bib
    Abdulsamad, H.; Peters, J. (2020). Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation, 2nd Annual Conference on Learning for Dynamics and Control.
  •   Bib
    Abdulsamad, H.; Peters, J. (2020). Learning Hybrid Dynamics and Control, ECML/PKDD Workshop on Deep Continuous-Discrete Machine Learning.
  •     Bib
    Abi-Farraj, F.; Pacchierotti, C.; Arenz, O.; Neumann, G.; Giordano, P. (2020). Haptic-based Guided Grasping in a Cluttered Environment, IEEE Haptics Symposium.
  •     Bib
    Agudelo-Espana, D.; Gomez-Gonzalez, S.; Bauer, S.; Schoelkopf, B.; Peters, J. (2020). Bayesian Online Prediction of Change Points, Conference on Uncertainty in Artificial Intelligence (UAI).
  •     Bib
    Almeida Santos, A.; Gil, C.E.M.; Peters, J.; Steinke, F. (2020). Decentralized Data-Driven Tuning of Droop Frequency Controllers, 2020 IEEE PES Innovative Smart Grid Technologies Europe.
  •     Bib
    Arenz, O.; Neumann, G. (2020). Non-Adversarial Imitation Learning and its Connections to Adversarial Methods, arXiv.
  •     Bib
    Arenz, O.; Zhong, M.; Neumann G. (2020). Trust-Region Variational Inference with Gaussian Mixture Models, Journal of Machine Learning Research (JMLR).
  •     Bib
    Becker, P.; Arenz, O.; Neumann, G. (2020). Expected Information Maximization: Using the I-Projection for Mixture Density Estimation, International Conference on Learning Representations (ICLR).
  •       Bib
    Dam, T.; Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2020). Generalized Mean Estimation in Monte-Carlo Tree Search, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).
  •     Bib
    D`Eramo, C.; Tateo, D.; Bonarini, A.; Restelli, M.; Peters, J. (2020). Sharing Knowledge in Multi-Task Deep Reinforcement Learning, International Conference in Learning Representations (ICLR).
  •     Bib
    Eilers, C.; Eschmann, J.; Menzenbach, R.; Belousov, B.; Muratore, F.; Peters, J. (2020). Underactuated Waypoint Trajectory Optimization for Light Painting Photography, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •   Bib
    Ewerton, M.; Arenz, O.; Peters, J. (2020). Assisted Teleoperation in Changing Environments with a Mixture of Virtual Guides, Advanced Robotics, 34.
  •     Bib
    Gomez-Gonzalez, S.; Neumann, G.; Schölkopf, B.; Peters, J. (2020). Adaptation and Robust Learning of Probabilistic Movement Primitives, IEEE Transactions on Robotics (T-Ro), 36, 2, pp.366-379.
  •     Bib
    Gomez-Gonzalez, S.; Prokudin, S.; Schölkopf, B.; Peters, J. (2020). Real Time Trajectory Prediction Using Deep Conditional Generative Models, IEEE Robotics and Automation Letters (ICRA/RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), 5, 2, pp.970-976.
  •     Bib
    Keller, L.; Tanneberg, D.; Stark, S.; Peters, J. (2020). Model-Based Quality-Diversity Search for Efficient Robot Learning, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2020). Self-Paced Deep Reinforcement Learning, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •       Bib
    Koert, D.; Kircher, M.; Salikutluk, V.; D'Eramo, C.; Peters, J. (2020). Multi-Channel Interactive Reinforcement Learning for Sequential Tasks, Frontiers in Robotics and AI Human-Robot Interaction.
  •   Bib
    Koert, D.; Trick, S.; Ewerton, M.; Lutter, M.; Peters, J. (2020). Incremental Learning of an Open-Ended Collaborative Skill Library, International Journal of Humanoid Robotics (IJHR), 17, 1.
  •     Bib
    Lauri, M.; Pajarinen, J.; Peters, J.; Frintrop, S. (2020). Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization, IEEE Robotics and Automation Letters (RA-L), 5, 4, pp.5323-5330.
  •     Bib
    Laux, M.; Arenz, O.; Pajarinen, J.; Peters, J. (2020). Deep Adversarial Reinforcement Learning for Object Disentangling, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020).
  •   Bib
    Lioutikov, R.; Maeda, G.; Veiga, F.F.; Kersting, K.; Peters, J. (2020). Learning Attribute Grammars for Movement Primitive Sequencing, International Journal of Robotics Research (IJRR), 39, 1, pp.21-38.
  •     Bib
    Loeckel, S.; Peters, J.; van Vliet, P. (2020). A Probabilistic Framework for Imitating Human Race Driver Behavior, IEEE Robotics and Automation Letters (RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), 5, 2.
  •   Bib
    Lutter, M.; Clever, D.; Belousov, B.; Listmann, K.; Peters, J. (2020). Evaluating the Robustness of HJB Optimal Feedback Control, International Symposium on Robotics.
  •   Bib
    Motokura, K.; Takahashi, M.; Ewerton, M.; Peters, J. (2020). Plucking Motions for Tea Harvesting Robots Using Probabilistic Movement Primitives, IEEE Robotics and Automation Letters (ICRA/RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), 5, 2, pp.2377-3766.
  •     Bib
    Ploeger, K.; Lutter, M.; Peters, J. (2020). High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards, Conference on Robot Learning (CoRL).
  •     Bib
    Prasad, V.; Stock-Homburg, R.; Peters, J. (2020). Advances in Human-Robot Handshaking, International Conference on Social Robotics, Springer.
  •     Bib
    Stock-Homburg, R.; Peters, J.; Schneider, K.; Prasad, V.; Nukovic, L. (2020). Evaluation of the Handshake Turing Test for anthropomorphic Robots, Proceedings of the ACM/IEEE International Conference on Human Robot Interaction (HRI), Late Breaking Report.
  •       Bib
    Tanneberg, D.; Rueckert, E.; Peters, J. (2020). Evolutionary Training and Abstraction Yields Algorithmic Generalization of Neural Computers, Nature Machine Intelligence, 2, 12, pp.753-763.
  •     Bib
    Tosatto, S.; Carvalho, J.; Abdulsamad, H.; Peters, J. (2020). A Nonparametric Off-Policy Policy Gradient, Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS).
  •     Bib
    Tosatto, S.; Stadtmueller, J.; Peters, J. (2020). Dimensionality Reduction of Movement Primitives in Parameter Space, arXiv.
  •     Bib
    Urain, J.; Ginesi, M.; Tateo, D.; Peters, J. (2020). ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows, IEEE/RSJ International Conference on Intelligent Robots and Systems.
  •     Bib
    Urain, J.; Tateo, D.; Ren, T.; Peters, J. (2020). Structured policy representation: Imposing stability in arbitrarily conditioned dynamic systems, NeurIPS 2020, 3rd Robot Learning Workshop, pp.7.
  •     Bib
    Veiga, F. F.; Akrour, R.; Peters, J. (2020). Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks, Frontiers in Robotics and AI.
  •     Bib
    Veiga, F. F.; Edin B.B; Peters, J. (2020). Grip Stabilization through Independent Finger Tactile Feedback Control, Sensors (Special Issue on Sensors and Robot Control), 20.
  •     Bib
    Vinogradska, J.; Bischoff, B.; Koller, T.; Achterhold, J.; Peters, J. (2020). Numerical Quadrature for Probabilistic Policy Search, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 42, 1, pp.164-175.
  •   Bib
    Watson, J.; Imohiosen A.; Peters, J. (2020). Active Inference or Control as Inference? A Unifying View, International Workshop on Active Inference.
  •     Bib
    Zelch, C.; Peters, J.; von Stryk, O. (2020). Learning Control Policies from Optimal Trajectories, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).

2019

  •   Bib
    Abdulsamad, H.; Naveh, K.; Peters, J. (2019). Model-Based Relative Entropy Policy Search for Stochastic Hybrid Systems, 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •       Bib
    Abi Farraj, F.; Pacchierotti, C.; Arenz, O.; Neumann, G.; Giordano, P. (2019). A Haptic Shared-Control Architecture for Guided Multi-Target Robotic Grasping, IEEE Transactions on Haptics.
  •     Bib
    Akrour, R.; Pajarinen, J.; Neumann, G.; Peters, J. (2019). Projections for Approximate Policy Iteration Algorithms, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Becker-Ehmck, P.; Peters, J.; van der Smagt, P. (2019). Switching Linear Dynamics for Variational Bayes Filtering, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Belousov, B.; Abdulsamad, H.; Schultheis, M.; Peters, J. (2019). Belief Space Model Predictive Control for Approximately Optimal System Identification, 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •       Bib
    Belousov, B.; Peters, J. (2019). Entropic Regularization of Markov Decision Processes, Entropy, 21, 7, MDPI.
  •     Bib
    Belousov, B.; Sadybakasov, A.; Wibranek, B.; Veiga, F.; Tessmann, O.; Peters, J. (2019). Building a Library of Tactile Skills Based on FingerVision, Proceedings of the 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids).
  •     Bib
    Brandherm, F.; Peters, J.; Neumann, G.; Akrour, R. (2019). Learning Replanning Policies with Direct Policy Search, IEEE Robotics and Automation Letters (RA-L).
  •     Bib
    Celemin, C.; Maeda, G.; Peters, J.; Ruiz-del-Solar, J.; Kober, J. (2019). Reinforcement Learning of Motor Skills using Policy Search and Human Corrective Advice, International Journal of Robotics Research (IJRR), 38, 14.
  •     Bib
    Celik, O.; Abdulsamad, H.; Peters, J. (2019). Chance-Constrained Trajectory Optimization for Nonlinear Systems with Unknown Stochastic Dynamics, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Delfosse, Q.; Stark, S.; Tanneberg, D.; Santucci, V. G.; Peters, J. (2019). Open-Ended Learning of Grasp Strategies using Intrinsically Motivated Self-Supervision, Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Ewerton, M.; Arenz, O.; Maeda, G.; Koert, D.; Kolev, Z.; Takahashi, M.; Peters, J. (2019). Learning Trajectory Distributions for Assisted Teleoperation and Path Planning, Frontiers in Robotics and AI.
  •     Bib
    Ewerton, M.; Maeda, G.; Koert, D.; Kolev, Z.; Takahashi, M.; Peters, J. (2019). Reinforcement Learning of Trajectory Distributions: Applications in Assisted Teleoperation and Motion Planning, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.4294--4300.
  •     Bib
    Gebhardt, G.H.W.; Kupcsik, A.; Neumann, G. (2019). The Kernel Kalman Rule, Machine Learning Journal (MLJ), 108, 12, pp.2113–2157, Springer US.
  •     Bib
    Gomez Gonzalez, S.; Nemmour, Y.; Schoelkopf, B.; Peters, J. (2019). Reliable Real Time Ball Tracking for Robot Table Tennis, Robotics, 8, 4.
  •     Bib
    Klink, P.; Abdulsamad, H.; Belousov, B.; Peters, J. (2019). Self-Paced Contextual Reinforcement Learning, Proceedings of the 3rd Conference on Robot Learning (CoRL).
  •   Bib
    Klink, P.; Peters, J. (2019). Measuring Similarities between Markov Decision Processes, 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Koc, O.; Maeda, G.; Peters, J. (2019). Optimizing the Execution of Dynamic Robot Movements with Learning Control, IEEE Transactions on Robotics, 35, 4, pp.1552-3098.
  •     Bib
    Koc, O.; Peters, J. (2019). Learning to serve: an experimental study for a new learning from demonstrations framework, IEEE Robotics and Automation Letters (ICRA/RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Koert, D.; Pajarinen, J.; Schotschneider, A.; Trick, S., Rothkopf, C.; Peters, J. (2019). Learning Intention Aware Online Adaptation of Movement Primitives, IEEE Robotics and Automation Letters (RA-L), with presentation at the IEEE International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Lauri, M.; Pajarinen, J.; Peters, J. (2019). Information gathering in decentralized POMDPs by policy graph improvement, Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS).
  •     Bib
    Liu, Z.; Hitzmann, A.; Ikemoto, S.; Stark, S.; Peters, J.; Hosoda, K. (2019). Local Online Motor Babbling: Learning Motor Abundance of a Musculoskeletal Robot Arm, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •   Bib
    Look, A.; Kandemir, M. (2019). Differential Bayesian Neural Nets, NeurIPS Bayesian Workshop.
  •     Bib
    Lutter, M.; Belousov, B.; Listmann, K.; Clever, D.; Peters, J. (2019). HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints, Conference on Robot Learning (CoRL).
  •     Bib
    Lutter, M.; Peters, J. (2019). Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems, International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Lutter, M.; Peters, J. (2019). Deep Optimal Control: Using the Euler-Lagrange Equation to learn an Optimal Feedback Control Law, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Lutter, M.; Ritter, C.; Peters, J. (2019). Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning, International Conference on Learning Representations (ICLR).
  •     Bib
    Muratore, F.; Gienger, M.; Peters, J. (2019). Assessing Transferability in Reinforcement Learning from Randomized Simulations, Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Nass, D.; Belousov, B.; Peters, J. (2019). Entropic Risk Measure in Policy Search, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •   Bib
    Ozdenizci, O.; Meyer, T.; Wichmann, F.; Peters, J.; Schölkopf B.; Cetin, M.; Grosse-Wentrup, M. (2019). “Neural Signatures of Motor Skill in the Resting Brain, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC).
  •     Bib
    Pajarinen, J.; Thai, H.L.; Akrour, R.; Peters, J.; Neumann, G. (2019). Compatible natural gradient policy search, Machine Learning (MLJ), 108, 8, pp.1443--1466, Springer.
  •     Bib
    Parisi, S.; Tangkaratt, V.; Peters, J.; Khan, M. E. (2019). TD-Regularized Actor-Critic Methods, Machine Learning (MLJ), 108, 8, pp.1467-1501.
  •   Bib
    Schuermann, T.; Mohler, B.J.; Peters, J.; Beckerle, P. (2019). How Cognitive Models of Human Body Experience Might Push Robotics, Frontiers in Neurorobotics.
  •     Bib
    Schultheis, M.; Belousov, B.; Abdulsamad, H.; Peters, J. (2019). Receding Horizon Curiosity, Proceedings of the 3rd Conference on Robot Learning (CoRL).
  •     Bib
    Stark, S.; Peters, J.; Rueckert, E. (2019). Experience Reuse with Probabilistic Movement Primitives, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Tanneberg, D.; Peters, J.; Rueckert, E. (2019). Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks, Neural Networks, 109, pp.67-80.
  •     Bib
    Tanneberg, D.; Rueckert, E.; Peters, J. (2019). Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer Architecture, arXiv.
  •     Bib
    Tosatto, S.; D'Eramo, C.; Pajarinen, J.; Restelli, M.; Peters, J. (2019). Exploration Driven By an Optimistic Bellman Equation, Proceedings of the International Joint Conference on Neural Networks (IJCNN).
  •     Bib
    Trick, S.; Koert, D.; Peters, J.; Rothkopf, C. (2019). Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Urain, J.; Peters, J. (2019). Generalized Multiple Correlation Coefficient as a Similarity Measurement between Trajectories, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Watson, J.; Abdulsamad, H.; Peters, J. (2019). Stochastic Optimal Control as Approximate Input Inference, Conference on Robot Learning (CoRL).
  •     Bib
    Wibranek, B.; Belousov, B.; Sadybakasov, A.; Peters, J.; Tessmann, O. (2019). Interactive Structure: Robotic Repositioning of Vertical Elements in Man-Machine Collaborative Assembly through Vision-Based Tactile Sensing, Proceedings of the 37th eCAADe and 23rd SIGraDi Conference.
  •     Bib
    Wibranek, B.; Belousov, B.; Sadybakasov, A.; Tessmann, O. (2019). Interactive Assemblies: Man-Machine Collaboration through Building Components for As-Built Digital Models, Computer-Aided Architectural Design Futures (CAAD Futures).

2018

  •     Bib
    Akrour, R.; Peters, J.; Neumann, G. (2018). Constraint-Space Projection Direct Policy Search, European Workshops on Reinforcement Learning (EWRL).
  •     Bib
    Akrour, R.; Veiga, F.; Peters, J.; Neumann, G. (2018). Regularizing Reinforcement Learning with State Abstraction, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Arenz, O.; Zhong, M.; Neumann, G. (2018). Efficient Gradient-Free Variational Inference using Policy Search, in: Dy, Jennifer and Krause, Andreas (eds.), Proceedings of the International Conference on Machine Learning (ICML), 80, pp.234--243, PMLR.
  •     Bib
    Belousov, B.; Peters, J. (2018). Entropic Regularization of Markov Decision Processes, 38th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering.
  •     Bib
    Belousov, B.; Peters, J. (2018). Mean Squared Advantage Minimization as a Consequence of Entropic Policy Improvement Regularization, European Workshops on Reinforcement Learning (EWRL).
  •     Bib
    Buechler, D.; Calandra, R.; Schoelkopf, B.; Peters, J. (2018). Control of Musculoskeletal Systems using Learned Dynamics Models, IEEE Robotics and Automation Letters, and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Ewerton, M.; Rother, D.; Weimar, J.; Kollegger, G.; Wiemeyer, J.; Peters, J.; Maeda, G. (2018). Assisting Movement Training and Execution with Visual and Haptic Feedback, Frontiers in Neurorobotics.
  •     Bib
    Gebhardt, G.H.W.; Daun, K.; Schnaubelt, M.; Neumann, G. (2018). Learning Robust Policies for Object Manipulation with Robot Swarms, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Gondaliya, K.D.; Peters, J.; Rueckert, E. (2018). Learning to Categorize Bug Reports with LSTM Networks, Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle.
  •     Bib
    Hoelscher, J.; Koert, D.; Peters, J.; Pajarinen, J. (2018). Utilizing Human Feedback in POMDP Execution and Specification, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Koc, O.; Maeda, G.; Peters, J. (2018). Online optimal trajectory generation for robot table tennis, Robotics and Autonomous Systems (RAS).
  •     Bib
    Koert, D.; Maeda, G.; Neumann, G.; Peters, J. (2018). Learning Coupled Forward-Inverse Models with Combined Prediction Errors, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Koert, D.; Trick, S.; Ewerton, M.; Lutter, M.; Peters, J. (2018). Online Learning of an Open-Ended Skill Library for Collaborative Tasks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Kroemer, O.; Leischnig, S.; Luettgen, S.; Peters, J. (2018). A Kernel-based Approach to Learning Contact Distributions for Robot Manipulation Tasks, Autonomous Robots (AURO), 42, 3, pp.581-600.
  •     Bib
    Lioutikov, R.; Maeda, G.; Veiga, F.F.; Kersting, K.; Peters, J. (2018). Inducing Probabilistic Context-Free Grammars for the Sequencing of Robot Movement Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Manschitz, S.; Gienger, M.; Kober, J.; Peters, J. (2018). Mixture of Attractors: A novel Movement Primitive Representation for Learning Motor Skills from Demonstrations, IEEE Robotics and Automation Letters (RA-L), 3, 2, pp.926-933.
  •       Bib
    Muratore, F.; Treede, F.; Gienger, M.; Peters, J. (2018). Domain Randomization for Simulation-Based Policy Optimization with Transferability Assessment, Conference on Robot Learning (CoRL).
  •     Bib
    Osa, T.; Pajarinen, J.; Neumann, G.; Bagnell, J.A.; Abbeel, P.; Peters, J. (2018). An Algorithmic Perspective on Imitation Learning, Foundations and Trends in Robotics.
  •     Bib
    Osa, T.; Peters, J.; Neumann, G. (2018). Hierarchical Reinforcement Learning of Multiple Grasping Strategies with Human Instructions, Advanced Robotics, 32, 18, pp.955-968.
  •     Bib
    Paraschos, A.; Daniel, C.; Peters, J.; Neumann, G. (2018). Using Probabilistic Movement Primitives in Robotics, Autonomous Robots (AURO), 42, 3, pp.529-551.
  •     Bib
    Paraschos, A.; Rueckert, E.; Peters, J.; Neumann, G. (2018). Probabilistic Movement Primitives under Unknown System Dynamics, Advanced Robotics (ARJ), 32, 6, pp.297-310.
  •   Bib
    Parmas, P.; Doya, K.; Rasmussen, C.; Peters, J. (2018). PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Pinsler, R.; Akrour, R.; Osa, T.; Peters, J.; Neumann, G. (2018). Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Pinsler, R.; Maag, M.; Arenz, O.; Neumann, G. (2018). Inverse Reinforcement Learning of Bird Flocking Behavior, Swarms: From Biology to Robotics and Back (ICRA Workshop).
  •   Bib
    Sosic, A.; Rueckert, E.; Peters, J.; Zoubir, A.M.; Koeppl, H (2018). Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling, Journal of Machine Learning Research (JMLR), 19, 69, pp.1--45.
  •     Bib
    Veiga, F.; Peters, J.; Hermans, T. (2018). Grip Stabilization of Novel Objects using Slip Prediction, IEEE Transactions on Haptics, 11, 4, pp.531--542.
  •     Bib
    Vinogradska, J.; Bischoff, B.; Peters, J. (2018). Approximate Value Iteration based on Numerical Quadrature, Proceedings of the International Conference on Robotics and Automation, and IEEE Robotics and Automation Letters (RA-L), 3, pp.1330-1337.
  •     Bib
    Yi, Z.; Zhang, Y.; Peters, J. (2018). Biomimetic Tactile Sensors and Signal Processing with Spike Trains: A Review, Sensors & Actuators: A. Physical, 269, pp.41-52.

2017

  •     Bib
    Abdulsamad, H.; Arenz, O.; Peters, J.; Neumann, G. (2017). State-Regularized Policy Search for Linearized Dynamical Systems, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS).
  •     Bib
    Akrour, R.; Sorokin, D.; Peters, J.; Neumann, G. (2017). Local Bayesian Optimization of Motor Skills, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Belousov, B.; Neumann, G.; Rothkopf, C.A.; Peters, J. (2017). Catching Heuristics Are Optimal Control Policies, Proceedings of the Karniel Thirteenth Computational Motor Control Workshop.
  •     Bib
    Belousov, B.; Peters, J. (2017). f-Divergence Constrained Policy Improvement, arXiv.
  •   Bib
    Busch, B.; Maeda, G.; Mollard, Y.; Demangeat, M.; Lopes, M. (2017). Postural Optimization for an Ergonomic Human-Robot Interaction, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Dermy, O.; Paraschos, A.; Ewerton, M.; Charpillet, F.; Peters, J.; Ivaldi, S (2017). Prediction of intention during interaction with iCub with Probabilistic Movement Primitives, Frontiers in Robotics and AI, 4, pp.45.
  •     Bib
    End, F.; Akrour, R.; Peters, J.; Neumann, G. (2017). Layered Direct Policy Search for Learning Hierarchical Skills, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Ewerton, M.; Kollegger, G.; Maeda, G.; Wiemeyer, J.; Peters, J. (2017). Iterative Feedback-basierte Korrekturstrategien beim Bewegungslernen von Mensch-Roboter-Dyaden, DVS Sportmotorik 2017.
  •     Bib
    Ewerton, M.; Maeda, G.; Rother, D.; Weimar, J.; Lotter, L.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2017). Assisting the practice of motor skills by humans with a probability distribution over trajectories, Workshop Human-in-the-loop robotic manipulation: on the influence of the human role at IROS 2017, Vancouver, Canada.
  •     Bib
    Farraj, F. B.; Osa, T.; Pedemonte, N.; Peters, J.; Neumann, G.; Giordano, P.R. (2017). A Learning-based Shared Control Architecture for Interactive Task Execution, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •   Bib
    Fiebig, K.H.; Jayaram, V.; Hesse, T.; Blank, A.; Peters, J.; Grosse-Wentrup, M. (2017). Bayesian Regression for Artifact Correction in Electroencephalography, Proceedings of the 7th Graz Brain-Computer Interface Conference.
  •     Bib
    Gabriel, A.; Akrour, R.; Peters, J.; Neumann, G. (2017). Empowered Skills, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •       Bib
    Gebhardt, G.H.W.; Daun, K.; Schnaubelt, M.; Hendrich, A.; Kauth, D.; Neumann, G. (2017). Learning to Assemble Objects with a Robot Swarm, Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pp.1547--1549, International Foundation for Autonomous Agents and Multiagent Systems.
  •     Bib
    Gebhardt, G.H.W.; Kupcsik, A.G.; Neumann, G. (2017). The Kernel Kalman Rule - Efficient Nonparametric Inference with Recursive Least Squares, Proceedings of the National Conference on Artificial Intelligence (AAAI).
  •   Bib
    Grossberger, L.; Hohmann, M.R.; Peters J.; Grosse-Wentrup, M. (2017). Investigating Music Imagery as a Cognitive Paradigm for Low-Cost Brain-Computer Interfaces, Proceedings of the 7th Graz Brain-Computer Interface Conference.
  •     Bib
    Ivaldi, S.; Lefort, S.; Peters, J.; Chetouani, M.; Provasi, J.; Zibetti, E. (2017). 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, International Journal of Social Robotics, 9, pp.63-86.
  •   Bib
    Kollegger, G., Wiemeyer, J., Ewerton, M. & Peters, J. (2017). BIMROB - Bidirectional Interaction between human and robot for the learning of movements - Robot trains human - Human trains robot, in: A. Schwirtz, F. Mess, Y. Demetriou & V. Senner (eds.), Inovation & Technologie im Sport - 23. Sportwissenschaftlicher Hochschultag der deutschen Vereinigung für Sportwissenschaft, pp.179, Czwalina-Feldhaus.
  •     Bib
    Kollegger, G.; Ewerton, M.; Wiemeyer, J.; Peters, J. (2017). BIMROB – Bidirectional Interaction between human and robot for the learning of movements – Robot trains human – Human trains robot, 23. Sport­wissenschaft­licher Hochschultag der dvs.
  •     Bib
    Kollegger, G.; Ewerton, M.; Wiemeyer, J.; Peters, J. (2017). BIMROB -- Bidirectional Interaction Between Human and Robot for the Learning of Movements, in: Lames, M.; Saupe, D.; Wiemeyer, J. (eds.), Proceedings of the 11th International Symposium on Computer Science in Sport (IACSS 2017), pp.151--163, Springer International Publishing.
  •     Bib
    Kollegger, G.; Reinhardt, N.; Ewerton, M.; Peters, J.; Wiemeyer, J. (2017). Die Bedeutung der Beobachtungsperspektive beim Bewegungslernen von Mensch-Roboter-Dyaden, DVS Sportmotorik 2017.
  •     Bib
    Kroemer, O.; Peters, J. (2017). A Comparison of Autoregressive Hidden Markov Models for Multi-Modal Manipulations with Variable Masses, Proceedings of the International Conference of Robotics and Automation, and IEEE Robotics and Automation Letters (RA-L), 2, 2, pp.1101 - 1108.
  •     Bib
    Kupcsik, A.G.; Deisenroth, M.P.; Peters, J.; Ai Poh, L.; Vadakkepat, V.; Neumann, G. (2017). Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills, Artificial Intelligence, 247, pp.415-439.
  •     Bib
    Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J. (2017). Learning Movement Primitive Libraries through Probabilistic Segmentation, International Journal of Robotics Research (IJRR), 36, 8, pp.879-894.
  •     Bib
    Maeda, G.; Ewerton, M.; Neumann, G.; Lioutikov, R.; Peters, J. (2017). Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot Collaboration, International Journal of Robotics Research (IJRR), 36, 13-14, pp.1579-1594.
  •     Bib
    Maeda, G.; Ewerton, M.; Osa, T.; Busch, B.; Peters, J. (2017). Active Incremental Learning of Robot Movement Primitives, Proceedings of the Conference on Robot Learning (CoRL).
  •     Bib
    Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Kroemer, O.; Peters, J. (2017). Probabilistic Movement Primitives for Coordination of Multiple Human-Robot Collaborative Tasks, Autonomous Robots (AURO), 41, 3, pp.593-612.
  •     Bib
    Osa, T.; Ghalamzan, E. A. M.; Stolkin, R.; Lioutikov, R.; Peters, J.; Neumann, G. (2017). Guiding Trajectory Optimization by Demonstrated Distributions, IEEE Robotics and Automation Letters (RA-L), 2, 2, pp.819-826, IEEE.
  •     Bib
    Padois, V.; Ivaldib, S.; Babič, J.; Mistry, M.; Peters, J.; Nori, F. (2017). Whole-body multi-contact motion in humans and humanoids, Robotics and Autonomous Systems, 90, pp.97-117.
  •     Bib
    Pajarinen, J.; Kyrki, V.; Koval, M.; Srinivasa, S; Peters, J.; Neumann, G. (2017). Hybrid Control Trajectory Optimization under Uncertainty, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Paraschos, A.; Lioutikov, R.; Peters, J.; Neumann, G. (2017). Probabilistic Prioritization of Movement Primitives, Proceedings of the International Conference on Intelligent Robot Systems, and IEEE Robotics and Automation Letters (RA-L).
  •     Bib
    Parisi, S.; Pirotta, M.; Peters, J. (2017). Manifold-based Multi-objective Policy Search with Sample Reuse, Neurocomputing, 263, pp.3-14.
  •     Bib
    Parisi, S.; Ramstedt, S.; Peters, J. (2017). Goal-Driven Dimensionality Reduction for Reinforcement Learning, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •   Bib
    Peters, J.; Lee, D.; Kober, J.; Nguyen-Tuong, D.; Bagnell, J.; Schaal, S. (2017). Chapter 15: Robot Learning, Springer Handbook of Robotics, 2nd Edition, pp.357-394, Springer International Publishing.
  •     Bib
    Rueckert, E.; Nakatenus, M.; Tosatto, S.; Peters, J. (2017). Learning Inverse Dynamics Models in O(n) time with LSTM networks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Stark, S.; Peters, J.; Rueckert, E. (2017). A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Tangkaratt, V.; van Hoof, H.; Parisi, S.; Neumann, G.; Peters, J.; Sugiyama, M. (2017). Policy Search with High-Dimensional Context Variables, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
  •     Bib
    Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals, Proceedings of the Conference on Robot Learning (CoRL).
  •     Bib
    Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Efficient Online Adaptation with Stochastic Recurrent Neural Networks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Thiem, S.; Stark, S.; Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Simulation of the underactuated Sake Robotics Gripper in V-REP, Workshop at the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Tosatto, S.; Pirotta, M.; D'Eramo, C; Restelli, M. (2017). Boosted Fitted Q-Iteration, Proceedings of the International Conference of Machine Learning (ICML).
  •     Bib
    van Hoof, H.; Neumann, G.; Peters, J. (2017). Non-parametric Policy Search with Limited Information Loss, Journal of Machine Learning Research (JMLR), 18, 73, pp.1-46.
  •     Bib
    van Hoof, H.; Tanneberg, D.; Peters, J. (2017). Generalized Exploration in Policy Search, Machine Learning (MLJ), 106, 9-10, pp.1705-1724.
  •     Bib
    Vinogradska, J.; Bischoff, B.; Nguyen-Tuong, D.; Peters, J. (2017). Stability of Controllers for Gaussian Process Forward Models, Journal of Machine Learning Research (JMLR), 18, 100, pp.1-37.
  •     Bib
    Wang, Z.; Boularias, A.; Muelling, K.; Schoelkopf, B.; Peters, J. (2017). Anticipatory Action Selection for Human-Robot Table Tennis, Artificial Intelligence, 247, pp.399-414.
  •     Bib
    Wiemeyer, J.; Peters, J.; Kollegger, G.; Ewerton, M. (2017). BIMROB – Bidirektionale Interaktion von Mensch und Roboter beim Bewegungslernen, DVS Sportmotorik 2017.
  •     Bib
    Wilbers, D.; Lioutikov, R.; Peters, J. (2017). Context-Driven Movement Primitive Adaptation, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Yi, Z.; Zhang, Y.; Peters, J. (2017). Bioinspired Tactile Sensor for Surface Roughness Discrimination, Sensors and Actuators A: Physical, 255, pp.46-53.

2016

  •     Bib
    Abdolmaleki, A.; Lau, N.; Reis, L.; Peters, J.; Neumann, G. (2016). Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller, Journal of Intelligent & Robotic Systems.
  •     Bib
    Akrour, R.; Abdolmaleki, A.; Abdulsamad, H.; Neumann, G. (2016). Model-Free Trajectory Optimization for Reinforcement Learning, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Arenz, O.; Abdulsamad, H.; Neumann, G. (2016). Optimal Control and Inverse Optimal Control by Distribution Matching, Proceedings of the International Conference on Intelligent Robots and Systems (IROS), IEEE.
  •     Bib
    Arenz, O.; Abdulsamad, H.; Neumann, G. (2016). (Inverse) Optimal Control for Matching Higher-Order Moments, DGR Days (Leipzig).
  •       Bib
    Arenz, O.; Neumann, G. (2016). Iterative Cost Learning from Different Types of Human Feedback, IROS 2016 Workshop on Human-Robot Collaboration.
  •     Bib
    Azad, M.; Ortenzi, V.; Lin, H., C.; Rueckert, E.; Mistry, M. (2016). Model Estimation and Control of Complaint Contact Normal Force, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Belousov, B.; Neumann, G.; Rothkopf, C.; Peters, J. (2016). Catching Heuristics Are Optimal Control Policies, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •   Bib
    Buechler, D.; Ott, H.; Peters, J. (2016). A Lightweight Robotic Arm with Pneumatic Muscles for Robot Learning, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Calandra, R.; Peters, J.; Rasmussen, C.E.; Deisenroth, M.P. (2016). Manifold Gaussian Processes for Regression, Proceedings of the International Joint Conference on Neural Networks (IJCNN).
  •     Bib
    Daniel, C.; Neumann, G.; Kroemer, O.; Peters, J. (2016). Hierarchical Relative Entropy Policy Search, Journal of Machine Learning Research (JMLR), 17, pp.1-50.
  •     Bib
    Daniel, C.; van Hoof, H.; Peters, J.; Neumann, G. (2016). Probabilistic Inference for Determining Options in Reinforcement Learning, Machine Learning (MLJ), 104, 2-3, pp.337-357.
  •     Bib
    Ewerton, M.; Maeda, G.; Neumann, G.; Kisner, V.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2016). Movement Primitives with Multiple Phase Parameters, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.201--206.
  •     Bib
    Ewerton, M.; Maeda, G.J.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2016). Incremental Imitation Learning of Context-Dependent Motor Skills, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp.351--358.
  •     Bib
    Fiebig, K.-H.; Jayaram, V.; Peters, J.; Grosse-Wentrup, M. (2016). Multi-Task Logistic Regression in Brain-Computer Interfaces, IEEE SMC 2016 — 6th Workshop on Brain-Machine Interface Systems.
  •   Bib
    Gomez-Gonzalez, S.; Neumann, G.; Schoelkopf, B.; Peters, J. (2016). Using Probabilistic Movement Primitives for Striking Movements, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •   Bib
    Huang, Y.; Buechler, D.; Koc, O.; Schoelkopf, B.; Peters, J. (2016). Jointly Learning Trajectory Generation and Hitting Point Prediction in Robot Table Tennis, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •   Bib
    Koc, O.; Peters, J.; Maeda, G. (2016). A New Trajectory Generation Framework in Robotic Table Tennis, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Koert, D.; Maeda, G.J.; Lioutikov, R.; Neumann, G.; Peters, J. (2016). Demonstration Based Trajectory Optimization for Generalizable Robot Motions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Kohlschuetter, J.; Peters, J.; Rueckert, E. (2016). Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities, Proceedings of the XIV Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON).
  •     Bib
    Kollegger, G.; Ewerton, M.; Peters, J.; Wiemeyer, J. (2016). Bidirektionale Interaktion zwischen Mensch und Roboter beim Bewegungslernen (BIMROB), 11. Symposium der DVS Sportinformatik.
  •   Bib
    Maeda, G.; Maloo, A.; Ewerton, M.; Lioutikov, R.; Peters, J. (2016). Proactive Human-Robot Collaboration with Interaction Primitives, International Workshop on Human-Friendly Robotics (HFR), Genoa, Italy.
  •     Bib
    Maeda, G.; Ewerton, M.; Koert, D; Peters, J. (2016). Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills, IEEE Robotics and Automation Letters (RA-L), 1, 2, pp.784--791.
  •     Bib
    Maeda, G.; Maloo, A.; Ewerton, M.; Lioutikov, R.; Peters, J. (2016). Anticipative Interaction Primitives for Human-Robot Collaboration, AAAI Fall Symposium Series. Shared Autonomy in Research and Practice, Arlington, VA, USA.
  •     Bib
    Manschitz, S.; Gienger, M.; Kober, J.; Peters, J. (2016). Probabilistic Decomposition of Sequential Force Interaction Tasks into Movement Primitives, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Modugno, V.; Neumann, G.; Rueckert, E.; Oriolo, G.; Peters, J.; Ivaldi, S. (2016). Learning soft task priorities for control of redundant robots, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Osa, T.; Peters, J.; Neumann, G. (2016). Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies, Proceedings of the International Symposium on Experimental Robotics (ISER).
  •     Bib
    Parisi, S; Blank, A; Viernickel T; Peters, J (2016). Local-utopia Policy Selection for Multi-objective Reinforcement Learning, Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).
  •   Bib
    Peters, J.; Bagnell, J.A. (2016). Policy gradient methods, Encyclopedia of Machine Learning, 2nd Edition, Invited Article.
  •   Bib
    Peters, J.; Tedrake, R.; Roy, N.; Morimoto, J. (2016). Robot Learning, Encyclopedia of Machine Learning, 2nd Edition, Invited Article.
  •       Bib
    Rueckert, E.; Camernik, J.; Peters, J.; Babic, J. (2016). Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control, Nature PG: Scientific Reports, 6, 28455.
  •       Bib
    Rueckert, E.; Kappel, D.; Tanneberg, D.; Pecevski, D; Peters, J. (2016). Recurrent Spiking Networks Solve Planning Tasks, Nature PG: Scientific Reports, 6, 21142, Nature Publishing Group.
  •     Bib
    Sharma, D.; Tanneberg, D.; Grosse-Wentrup, M.; Peters, J.; Rueckert, E. (2016). Adaptive Training Strategies for BCIs, Cybathlon Symposium.
  •     Bib
    Tanneberg, D.; Paraschos, A.; Peters, J.; Rueckert, E. (2016). Deep Spiking Networks for Model-based Planning in Humanoids, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    van Hoof, H.; Chen, N.; Karl, M.; van der Smagt, P.; Peters, J. (2016). Stable Reinforcement Learning with Autoencoders for Tactile and Visual Data, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Veiga, F.F.; Peters, J. (2016). Can Modular Finger Control for In-Hand Object Stabilization be accomplished by Independent Tactile Feedback Control Laws?, arXiv.
  •     Bib
    Vinogradska, J.; Bischoff, B.; Nguyen-Tuong, D.; Romer, A.; Schmidt, H.; Peters, J. (2016). Stability of Controllers for Gaussian Process Forward Models, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Weber, P.; Rueckert, E.; Calandra, R.; Peters, J.; Beckerle, P. (2016). A Low-cost Sensor Glove with Vibrotactile Feedback and Multiple Finger Joint and Hand Motion Sensing for Human-Robot Interaction, Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
  •     Bib
    Yi, Z.; Calandra, R.; Veiga, F.; van Hoof, H.; Hermans, T.; Zhang, Y.; Peters, J. (2016). Active Tactile Object Exploration with Gaussian Processes, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •   Bib
    Yi, Z.; Zhang, Y.; Peters, J. (2016). Surface Roughness Discrimination Using Bioinspired Tactile Sensors, Proceedings of the 16th International Conference on Biomedical Engineering.

2015

  •     Bib
    Abdolmaleki, A.; Lioutikov, R.; Peters, J; Lau, N.; Reis, L.; Neumann, G. (2015). Model-Based Relative Entropy Stochastic Search, Advances in Neural Information Processing Systems (NIPS / NeurIPS), MIT Press.
  •     Bib
    Calandra, R.; Ivaldi, S.; Deisenroth, M.; Peters, J. (2015). Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Calandra, R.; Ivaldi, S.; Deisenroth, M.;Rueckert, E.; Peters, J. (2015). Learning Inverse Dynamics Models with Contacts, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •       Bib
    Calandra, R.; Seyfarth, A.; Peters, J.; Deisenroth, M. (2015). Bayesian Optimization for Learning Gaits under Uncertainty, Annals of Mathematics and Artificial Intelligence (AMAI).
  •     Bib
    Daniel, C.; Kroemer, O.; Viering, M.; Metz, J.; Peters, J. (2015). Active Reward Learning with a Novel Acquisition Function, Autonomous Robots (AURO), 39, pp.389-405.
  •   Bib
    Dann, C.; Neumann, G.; Peters, J. (2015). Policy Evaluation with Temporal Differences: A Survey and Comparison, Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling (ICAPS), pp.359-360.
  •     Bib
    Ewerton, M.; Maeda, G.J.; Peters, J.; Neumann, G. (2015). Learning Motor Skills from Partially Observed Movements Executed at Different Speeds, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp.456--463.
  •     Bib
    Ewerton, M.; Neumann, G.; Lioutikov, R.; Ben Amor, H.; Peters, J.; Maeda, G. (2015). Learning Multiple Collaborative Tasks with a Mixture of Interaction Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.1535--1542.
  •     Bib
    Ewerton, M.; Neumann, G.; Lioutikov, R.; Ben Amor, H.; Peters, J.; Maeda, G. (2015). Modeling Spatio-Temporal Variability in Human-Robot Interaction with Probabilistic Movement Primitives, Workshop on Machine Learning for Social Robotics, ICRA.
  •     Bib
    Fritsche, L.; Unverzagt, F.; Peters, J.; Calandra, R. (2015). First-Person Tele-Operation of a Humanoid Robot, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Hoelscher, J.; Peters, J.; Hermans, T. (2015). Evaluation of Interactive Object Recognition with Tactile Sensing, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Huang, Y.; Schoelkopf, B.; Peters, J. (2015). Learning Optimal Striking Points for A Ping-Pong Playing Robot, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •   Bib
    Koc, O.; Maeda, G.; Neumann, G.; Peters, J. (2015). Optimizing Robot Striking Movement Primitives with Iterative Learning Control, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Kroemer, O.; Daniel, C.; Neumann, G; van Hoof, H.; Peters, J. (2015). Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Leischnig, S.; Luettgen, S.; Kroemer, O.; Peters, J. (2015). A Comparison of Contact Distribution Representations for Learning to Predict Object Interactions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Lioutikov, R.; Neumann, G.; Maeda, G.J.; Peters, J. (2015). Probabilistic Segmentation Applied to an Assembly Task, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Lopes, M.; Peters, J.; Piater, J.; Toussaint, M.; Baisero, A.; Busch, B.; Erkent, O.; Kroemer, O.; Lioutikov, R.; Maeda, G.; Mollard, Y.; Munzer, T.; Shukla, D. (2015). Semi-Autonomous 3rd-Hand Robot, Workshop on Cognitive Robotics in Future Manufacturing Scenarios, European Robotics Forum, Vienna, Austria.
  •     Bib
    Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Peters, J. (2015). A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives with Phase Estimation, Proceedings of the International Symposium of Robotics Research (ISRR).
  •     Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2015). Probabilistic Progress Prediction and Sequencing of Concurrent Movement Primitives, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2015). Learning Movement Primitive Attractor Goals and Sequential Skills from Kinesthetic Demonstrations, Robotics and Autonomous Systems, 74, pp.97-107.
  •     Bib
    Mariti, C.; Muscolo, G.G.; Peters, J.; Puig, D.; Recchiuto, C.T.; Sighieri, C.; Solanas, A.; von Stryk, O. (2015). Developing biorobotics for veterinary research into cat movements, Journal of Veterinary Behavior: Clinical Applications and Research, 10, pp.248-254.
  •     Bib
    Paraschos, A.; Rueckert, E.; Peters, J; Neumann, G. (2015). Model-Free Probabilistic Movement Primitives for Physical Interaction, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Parisi, S.; Abdulsamad, H.; Paraschos, A.; Daniel, C.; Peters, J. (2015). Reinforcement Learning vs Human Programming in Tetherball Robot Games, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Rueckert, E.; Lioutikov, R.; Calandra, R.; Schmidt, M.; Beckerle, P.; Peters, J. (2015). Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations, ICRA 2015 Workshop on Tactile and force sensing for autonomous compliant intelligent robots.
  •     Bib
    Rueckert, E.; Mundo, J.; Paraschos, A.; Peters, J.; Neumann, G. (2015). Extracting Low-Dimensional Control Variables for Movement Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Traversaro, S.; Del Prete, A.; Ivaldi, S.; Nori, F. (2015). Avoiding to rely on Inertial Parameters in Estimating Joint Torques with proximal F/T sensing, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •       Bib
    van Hoof, H.; Hermans, T.; Neumann, G.; Peters, J. (2015). Learning Robot In-Hand Manipulation with Tactile Features, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    van Hoof, H.; Peters, J.; Neumann, G. (2015). Learning of Non-Parametric Control Policies with High-Dimensional State Features, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
  •     Bib
    Veiga, F.F.; van Hoof, H.; Peters, J.; Hermans, T. (2015). Stabilizing Novel Objects by Learning to Predict Tactile Slip, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Wahrburg, A.; Zeiss, S.; Matthias, B.; Peters, J.; Ding, H. (2015). Combined Pose-Wrench and State Machine Representation for Modeling Robotic Assembly Skills, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).

2014

  •     Bib
    Ben Amor, H.; Neumann, G.; Kamthe, S.; Kroemer, O.; Peters, J. (2014). Interaction Primitives for Human-Robot Cooperation Tasks , Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •   Bib
    Ben Amor, H.; Saxena, A.; Hudson, N.; Peters, J. (2014). Special issue on autonomous grasping and manipulation, Autonomous Robots (AURO).
  •     Bib
    Bischoff, B.; Nguyen-Tuong, D.; van Hoof, H. McHutchon, A.; Rasmussen, C.E.; Knoll, A.; Peters, J.; Deisenroth, M.P. (2014). Policy Search For Learning Robot Control Using Sparse Data, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Bocsi, B.; Csato, L.; Peters, J. (2014). Indirect Robot Model Learning for Tracking Control, Advanced Robotics.
  •     Bib
    Brandl, S.; Kroemer, O.; Peters, J. (2014). Generalizing Pouring Actions Between Objects using Warped Parameters, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Calandra, R.; Gopalan, N.; Seyfarth, A.; Peters, J.; Deisenroth, M.P. (2014). Bayesian Gait Optimization for Bipedal Locomotion, Proceedings of the 2014 Learning and Intelligent Optimization Conference (LION8).
  •     Bib
    Calandra, R.; Seyfarth, A.; Peters, J.; Deisenroth, M.P. (2014). An Experimental Comparison of Bayesian Optimization for Bipedal Locomotion, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Chebotar, Y.; Kroemer, O.; Peters, J. (2014). Learning Robot Tactile Sensing for Object Manipulation, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Colome, A.; Neumann, G.; Peters, J.; Torras, C. (2014). Dimensionality Reduction for Probabilistic Movement Primitives, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Daniel, C.; Viering, M.; Metz, J.; Kroemer, O.; Peters, J. (2014). Active Reward Learning, Proceedings of Robotics: Science & Systems (R:SS).
  •     Bib
    Dann, C.; Neumann, G.; Peters, J. (2014). Policy Evaluation with Temporal Differences: A Survey and Comparison, Journal of Machine Learning Research (JMLR), 15, March, pp.809-883.
  •     Bib
    Deisenroth, M.P.; Englert, P.; Peters, J.; Fox, D. (2014). Multi-Task Policy Search for Robotics, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Deisenroth, M.P.; Fox, D.; Rasmussen, C.E. (2014). Gaussian Processes for Data-Efficient Learning in Robotics and Control, IEEE Transactions on Pattern Analysis and Machine Intelligence.
  •     Bib
    Droniou, A.; Ivaldi, S.; Sigaud, O. (2014). Deep unsupervised network for multimodal perception, representation and classification, Robotics and Autonomous Systems.
  •     Bib
    Gomez, V.; Kappen, B; Peters, J.; Neumann, G (2014). Policy Search for Path Integral Control, Proceedings of the European Conference on Machine Learning (ECML).
  •     Bib
    Haji Ghassemi, N.; Deisenroth, M.P. (2014). Approximate Inference for Long-Term Forecasting with Periodic Gaussian Processes, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
  •     Bib
    Hermans, T.; Veiga, F.; Hölscher, J.; van Hoof, H.; Peters, J. (2014). Demonstration: Learning for Tactile Manipulation, Advances in Neural Information Processing Systems (NIPS/NeurIPS), Demonstration Track., MIT Press.
  •     Bib
    Ivaldi, S.; Peters, J.; Padois, V.; Nori, F. (2014). Tools for simulating humanoid robot dynamics: a survey based on user feedback, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Kamthe, S.; Peters, J.; Deisenroth, M. (2014). Multi-modal filtering for non-linear estimation, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
  •   Bib
    Kober, J.; Peters, J. (2014). Learning Motor Skills - From Algorithms to Robot Experiments, Springer Tracts in Advanced Robotics 97 (STAR Series), Springer .
  •     Bib
    Kroemer, O.; Peters, J. (2014). Predicting Object Interactions from Contact Distributions, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Kroemer, O.; van Hoof, H.; Neumann, G.; Peters, J. (2014). Learning to Predict Phases of Manipulation Tasks as Hidden States, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Lioutikov, R.; Kroemer, O.; Peters, J.; Maeda, G. (2014). Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot, Proceedings of the 13th International Conference on Intelligent Autonomous Systems (IAS).
  •     Bib
    Lioutikov, R.; Paraschos, A.; Peters, J.; Neumann, G. (2014). Generalizing Movements with Information Theoretic Stochastic Optimal Control, Journal of Aerospace Information Systems, 11, 9, pp.579-595.
  •     Bib
    Lioutikov, R.; Paraschos, A.; Peters, J.; Neumann, G. (2014). Sample-Based Information-Theoretic Stochastic Optimal Control, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Luck, K.S.; Neumann, G.; Berger, E.; Peters, J.; Ben Amor, H. (2014). Latent Space Policy Search for Robotics, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Maeda, G.J.; Ewerton, M.; Lioutikov, R.; Amor, H.B.; Peters, J.; Neumann, G. (2014). Learning Interaction for Collaborative Tasks with Probabilistic Movement Primitives, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp.527--534.
  •   Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2014). Learning to Unscrew a Light Bulb from Demonstrations, Proceedings of ISR/ROBOTIK 2014.
  •     Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2014). Learning to Sequence Movement Primitives from Demonstrations, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Meyer, T.; Peters, J.; Zander, T.O.; Schoelkopf, B.; Grosse-Wentrup, M. (2014). Predicting Motor Learning Performance from Electroencephalographic Data, Journal of Neuroengineering and Rehabilitation, 11, 1.
  •     Bib
    Muelling, K.; Boularias, A.; Schoelkopf, B.; Peters, J. (2014). Learning Strategies in Table Tennis using Inverse Reinforcement Learning, Biological Cybernetics, 108, 5, pp.603-619.
  •     Bib
    Neumann, G.; Daniel, C.; Paraschos, A.; Kupcsik, A.; Peters, J. (2014). Learning Modular Policies for Robotics, Frontiers in Computational Neuroscience.
  •     Bib
    Nori, F.; Peters, J.; Padois, V.; Babic, J.; Mistry, M.; Ivaldi, S. (2014). Whole-body motion in humans and humanoids, Proceedings of the Workshop on New Research Frontiers for Intelligent Autonomous Systems (NRF-IAS), pp.81-92.
  •     Bib
    Rueckert, E.; Mindt, M.; Peters, J.; Neumann, G. (2014). Robust Policy Updates for Stochastic Optimal Control, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Saut, J.-P.; Ivaldi, S.; Sahbani, A.; Bidaud, P. (2014). Grasping objects localized from uncertain point cloud data, Robotics and Autonomous Systems.
  •       Bib
    van Hoof, H.; Kroemer, O; Peters, J. (2014). Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments, IEEE Transactions on Robotics (TRo), 30, 5, pp.1198-1209.
  •     Bib
    Wierstra, D.; Schaul, T.; Glasmachers, T.; Sun, Y.; Peters, J.; Schmidhuber, J. (2014). Natural Evolution Strategies, Journal of Machine Learning Research (JMLR), 15, March, pp.949-980.

2013

  •     Bib
    Ben Amor, H.; Vogt, D.; Ewerton, M.; Berger, E.; Jung, B.; Peters, J. (2013). Learning Responsive Robot Behavior by Imitation, Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Berger, E.; Vogt, D.; Haji-Ghassemi, N.; Jung, B.; Ben Amor, H. (2013). Inferring Guidance Information in Cooperative Human-Robot Tasks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •       Bib
    Bocsi, B.; Csato, L.; Peters, J. (2013). Alignment-based Transfer Learning for Robot Models, Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN) .
  •       Bib
    Daniel, C.; Neumann, G.; Kroemer, O.; Peters, J. (2013). Learning Sequential Motor Tasks, Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA).
  •   Bib
    Daniel, C.; Neumann, G.; Peters, J. (2013). Autonomous Reinforcement Learning with Hierarchical REPS, Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN) .
  •       Bib
    Deisenroth, M. P.; Neumann, G.; Peters, J. (2013). A Survey on Policy Search for Robotics, Foundations and Trends in Robotics, 21, pp.388-403.
  •       Bib
    Englert, P.; Paraschos, A.; Peters, J.; Deisenroth, M. P. (2013). Model-based Imitation Learning by Probabilistic Trajectory Matching, Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Englert, P.; Paraschos, A.; Peters, J.;Deisenroth, M.P. (2013). Probabilistic Model-based Imitation Learning, Adaptive Behavior Journal, 21, pp.388-403.
  •       Bib
    Gopalan, N.; Deisenroth, M. P.; Peters, J. (2013). Feedback Error Learning for Rhythmic Motor Primitives, Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Kober, J.; Bagnell, D.; Peters, J. (2013). Reinforcement Learning in Robotics: A Survey, International Journal of Robotics Research (IJRR), 32, 11, pp.1238-1274.
  •       Bib
    Kupcsik, A.G.; Deisenroth, M.P.; Peters, J.; Neumann, G. (2013). Data-Efficient Generalization of Robot Skills with Contextual Policy Search, Proceedings of the National Conference on Artificial Intelligence (AAAI) .
  •       Bib
    Muelling, K.; Kober, J.; Kroemer, O.; Peters, J. (2013). Learning to Select and Generalize Striking Movements in Robot Table Tennis, International Journal of Robotics Research (IJRR), 32, 3, pp.263-279.
  •   Bib
    Neumann, G.; Kupcsik, A.G.; Deisenroth, M.P.; Peters, J. (2013). Information-Theoretic Motor Skill Learning, Proceedings of the AAAI 2013 Workshop on Intelligent Robotic Systems.
  •     Bib
    Paraschos, A.; Daniel, C.; Peters, J.; Neumann, G (2013). Probabilistic Movement Primitives, Advances in Neural Information Processing Systems (NIPS / NeurIPS), MIT Press.
  •     Bib
    Paraschos, A.; Neumann, G; Peters, J. (2013). A Probabilistic Approach to Robot Trajectory Generation, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •       Bib
    Peters, J.; Kober, J.; Muelling, K.; Kroemer, O.; Neumann, G. (2013). Towards Robot Skill Learning: From Simple Skills to Table Tennis, Proceedings of the European Conference on Machine Learning (ECML), Nectar Track.
  •   Bib
    Peters, J.; Kober, J.; Muelling, K.; Nguyen-Tuong, D.; Kroemer, O. (2013). Learning Skills with Motor Primitives, Proceedings of the 16th Yale Learning Workshop.
  •     Bib
    van Hoof, H.; Kroemer, O; Peters, J. (2013). Probabilistic Interactive Segmentation for Anthropomorphic Robots in Cluttered Environments , Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •       Bib
    Wang, Z.; Muelling, K.; Deisenroth, M. P.; Ben Amor, H.; Vogt, D.; Schoelkopf, B.; Peters, J. (2013). Probabilistic Movement Modeling for Intention Inference in Human-Robot Interaction, International Journal of Robotics Research (IJRR), 32, 7, pp.841-858.

2012

  •       Bib
    Ben Amor, H.; Kroemer, O.; Hillenbrand, U.; Neumann, G.; Peters, J. (2012). Generalization of Human Grasping for Multi-Fingered Robot Hands, Proceedings of the International Conference on Robot Systems (IROS).
  •       Bib
    Bocsi, B.; Hennig, P.; Csato, L.; Peters, J. (2012). Learning Tracking Control with Forward Models, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •       Bib
    Boularias, A.; Kroemer, O.; Peters, J. (2012). Structured Apprenticeship Learning, Proceedings of the European Conference on Machine Learning (ECML).
  •       Bib
    Boularias, A.; Kroemer, O.; Peters, J. (2012). Algorithms for Learning Markov Field Policies, Advances in Neural Information Processing Systems 26 (NIPS/NeurIPS), Cambridge, MA: MIT Press., MIT Press.
  •     Bib
    Calandra, R.; Raiko, T.; Deisenroth, M.P.; Montesino Pouzols, F. (2012). Learning Deep Belief Networks from Non-Stationary Streams, International Conference on Artificial Neural Networks (ICANN).
  •       Bib
    Daniel, C.; Neumann, G.; Peters, J. (2012). Hierarchical Relative Entropy Policy Search, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2012).
  •       Bib
    Daniel, C.; Neumann, G.; Peters, J. (2012). Learning Concurrent Motor Skills in Versatile Solution Spaces, Proceedings of the International Conference on Robot Systems (IROS).
  •       Bib
    Deisenroth M. P.; Szepesvari C.; Peters J. (2012)., in: Deisenroth M. P.; Szepesvari C., Peters J. (eds.), Proceedings of the 10th European Workshop on Reinforcement Learning, 24.
  •       Bib
    Deisenroth, M.P.; Calandra, R.; Seyfarth, A.; Peters, J. (2012). Toward Fast Policy Search for Learning Legged Locomotion, Proceedings of the International Conference on Robot Systems (IROS).
  •     Bib
    Deisenroth, M.P.; Mohamed, S. (2012). Expectation Propagation in Gaussian Process Dynamical Systems, Advances in Neural Information Processing Systems 26 (NIPS/NeurIPS), Cambridge, MA: MIT Press., The MIT Press.
  •     Bib
    Deisenroth, M.P.; Peters, J. (2012). Solving Nonlinear Continuous State-Action-Observation POMDPs for Mechanical Systems with Gaussian Noise, Proceedings of the European Workshop on Reinforcement Learning (EWRL).
  •     Bib
    Deisenroth, M.P.; Turner, R.; Huber, M.; Hanebeck, U.D.; Rasmussen, C.E (2012). Robust Filtering and Smoothing with Gaussian Processes, IEEE Transactions on Automatic Control.
  •       Bib
    Kober, J.; Wilhelm, A.; Oztop, E.; Peters, J. (2012). Reinforcement Learning to Adjust Parametrized Motor Primitives to New Situations, Autonomous Robots (AURO), 33, 4, pp.361-379, Springer US.
  •       Bib
    Kober, J; Muelling, K.; Peters, J. (2012). Learning Throwing and Catching Skills, Proceedings of the International Conference on Robot Systems (IROS), Video Track.
  •       Bib
    Kroemer, O.; Ben Amor, H.; Ewerton, M.; Peters, J. (2012). Point Cloud Completion Using Extrusions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •       Bib
    Kroemer, O.; Ugur, E.; Oztop, E. ; Peters, J. (2012). A Kernel-based Approach to Direct Action Perception, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •       Bib
    Lampert, C.H.; Peters, J. (2012). Real-Time Detection of Colored Objects In Multiple Camera Streams With Off-the-Shelf Hardware Components, Journal of Real-Time Image Processing, 7, 1, pp.31-41.
  •   Bib
    Meyer, T.; Peters, J.; Broetz, D.; Zander, T.; Schoelkopf, B.; Soekadar, S.; Grosse-Wentrup, M. (2012). Investigating the Neural Basis for Stroke Rehabilitation by Brain-Computer Interfaces, International Conference on Neurorehabilitation.
  •       Bib
    Meyer, T.; Peters, J.;Broetz, D.; Zander, T.; Schoelkopf, B.; Soekadar, S.; Grosse-Wentrup, M. (2012). A Brain-Robot Interface for Studying Motor Learning after Stroke, Proceedings of the International Conference on Robot Systems (IROS).
  •       Bib
    Muelling, K.; Kober, J.; Kroemer, O.; Peters, J. (2012). Learning to Select and Generalize Striking Movements in Robot Table Tennis, Proceedings of the AAAI 2012 Fall Symposium on Robots that Learn Interactively from Human Teachers.
  •       Bib
    Nguyen-Tuong, D.; Peters, J. (2012). Online Kernel-based Learning for Task-Space Tracking Robot Control, IEEE Transactions on Neural Networks and Learning Systems, 23, 9, pp.1417-1425 .
  •       Bib
    Peters, J.; Kober, J.; Muelling, K.; Nguyen-Tuong, D.; Kroemer, O. (2012). Robot Skill Learning, Proceedings of the European Conference on Artificial Intelligence (ECAI).
  •     Bib
    Sigaud, O.; Peters, J. (2012). Robot Learning, Encyclopedia of the Sciences of Learning, Springer Verlag, Springer Verlag.
  •       Bib
    van Hoof, H.; Kroemer, O.;Ben Amor, H.; Peters, J. (2012). Maximally Informative Interaction Learning for Scene Exploration, Proceedings of the International Conference on Robot Systems (IROS).
  •       Bib
    Vitzthum, A.; Ben Amor, H.; Heumer, G.; Jung, B. (2012). XSAMPL3D - An Action Description Language for the Animation of Virtual Characters, Journal of Virtual Reality and Broadcasting, 9, 1.
  •       Bib
    Wang, Z.;Deisenroth, M; Ben Amor, H.; Vogt, D.; Schoelkopf, B.; Peters, J. (2012). Probabilistic Modeling of Human Movements for Intention Inference, Proceedings of Robotics: Science and Systems (R:SS).

2011

  •       Bib
    Bocsi, B.; Nguyen-Tuong, D; Csato, L; Schoelkopf, B.; Peters, J. (2011). Learning Inverse Kinematics with Structured Prediction, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
  •     Bib
    Boularias, A.; Kober, J.; Peters, J. (2011). Relative Entropy Inverse Reinforcement Learning, Proceedings of Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2011).
  •       Bib
    Boularias, A.; Kroemer, O.; Peters, J. (2011). Learning Robot Grasping from 3D Images with Markov Random Fields, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
  •     Bib
    Detry, R.; Kraft, D.; Kroemer, O.; Peters, J.; Krueger, N.; Piater, J.; (2011). Learning Grasp Affordance Densities, Paladyn Journal of Behavioral Robotics, 2, 1, pp.1-17.
  •       Bib
    Gomez Rodriguez, M.; Grosse-Wentrup, M.; Hill, J.; Schoelkopf, B.; Gharabaghi, A.; Peters, J. (2011). Towards Brain-Robot Interfaces for Stroke Rehabilitation, Proceedings of the International Conference on Rehabilitation Robotics (ICORR).
  •     Bib
    Gomez Rodriguez, M.; Peters, J.; Hill, J.; Schoelkopf, B.; Gharabaghi, A.; Grosse-Wentrup, M. (2011). Closing the Sensorimotor Loop: Haptic Feedback Helps Decoding of Motor Imagery, Journal of Neuroengineering, 8, 3.
  •       Bib
    Hachiya, H.; Peters, J.; Sugiyama, M. (2011). Reward Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning, Neural Computation, 23, 11.
  •     Bib
    Kober, J.; Oztop, E.; Peters, J. (2011). Reinforcement Learning to adjust Robot Movements to New Situations, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Best Paper Track.
  •       Bib
    Kober, J.; Peters, J. (2011). Policy Search for Motor Primitives in Robotics, Machine Learning (MLJ), 84, 1-2, pp.171-203.
  •       Bib
    Kober, J.; Peters, J. (2011). Learning Elementary Movements Jointly with a Higher Level Task, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
  •     Bib
    Kroemer, O.; Lampert, C.H.; Peters, J. (2011). Learning Dynamic Tactile Sensing with Robust Vision-based Training, IEEE Transactions on Robotics (T-Ro), 27, 3, pp.545-557.
  •     Bib
    Kroemer, O.; Peters, J. (2011). A Flexible Hybrid Framework for Modeling Complex Manipulation Tasks, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Kroemer, O.; Peters, J. (2011). Active Exploration for Robot Parameter Selection in Episodic Reinforcement Learning, Proceedings of the 2011 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL).
  •       Bib
    Kroemer, O.; Peters, J. (2011). A Non-Parametric Approach to Dynamic Programming, Advances in Neural Information Processing Systems 25 (NIPS/NeurIPS), MIT Press.
  •     Bib
    Lampariello, R.; Nguyen Tuong, D.; Castellini, C.; Hirzinger, G.; Peters, J. (2011). Energy-optimal robot catching in real-time, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Muelling, K.; Kober, J.; Peters, J. (2011). A Biomimetic Approach to Robot Table Tennis, Adaptive Behavior Journal, 19, 5.
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2011). Incremental Sparsification for Real-time Online Model Learning, Neurocomputing, 74, 11, pp.1859-1867.
  •       Bib
    Nguyen Tuong, D.; Peters, J. (2011). Learning Task-Space Tracking Control with Kernels, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2011). Model Learning in Robotics: a Survey, Cognitive Processing, 12, 4.
  •     Bib
    Piater, J.; Jodogne, S.; Detry, R.; Kraft, D.; Krueger, N.; Kroemer, O.; Peters, J. (2011). Learning Visual Representations for Perception-Action Systems, International Journal of Robotics Research (IJRR), 30, 3, pp.294-307.
  •       Bib
    van Hoof, H.; van der Zant, T. ; Wiering, M.A. (2011). Adaptive Visual Face Tracking for an Autonomous Robot, Proceedings of the Belgian-Dutch Artificial Intelligence Conference (BNAIC 11).
  •     Bib
    Wang, Z.; Boularias, A.; Muelling, K.; Peters, J. (2011). Balancing Safety and Exploitability in Opponent Modeling, Proceedings of the Twenty-Fifth National Conference on Artificial Intelligence (AAAI).
  •       Bib
    Wang, Z.; Lampert, C; Muelling, K; Schoelkopf, B.; Peters, J. (2011). Learning Anticipation Policies for Robot Table Tennis, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).

2010

  •     Bib
    Alvaro, M.; Peters, J.; Schoelfkopf, B.; Lawrence, N. (2010). Switched Latent Force Models for Movement Segmentation, Advances in Neural Information Processing Systems 24 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
  •     Bib
    Chiappa, S.; Peters, J. (2010). Movement extraction by detecting dynamics switches and repetitions, Advances in Neural Information Processing Systems 24 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
  •     Bib
    Detry, R.; Baseski, E.; Popovic, M.; Touati, Y.; Krueger, N.; Kroemer, O.; Peters, J.; Piater, J. (2010). Learning Continuous Grasp Affordances by Sensorimotor Exploration, From Motor Learning to Interaction Learning in Robots, Springer Verlag, 264.
  •       Bib
    Erkan, A.: Kroemer, O.; Detry, R.; Altun, Y.; Piater, J.; Peters, J. (2010). Learning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Gomez Rodriguez, M.; Grosse Wentrup, M.; Peters, J.; Naros, G.; Hill, J.; Gharabaghi, A.; Schoelkopf, B. (2010). Epidural ECoG Online Decoding of Arm Movement Intention in Hemiparesis, 1st ICPR Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging.
  •     Bib
    Gomez Rodriguez, M.; Peters, J.; Hill, J.; Gharabaghi, A.; Schoelkopf, B.; Grosse-Wentrup, M. (2010). BCI and robotics framework for stroke rehabilitation, Proceedings of the 4th International BCI Meeting, May 31 - June 4, 2010. Asilomar, CA, USA.
  •     Bib
    Gomez Rodriguez, M.; Peters, J.; Hill, J.; Schoelkopf, B.; Gharabaghi, A.; Grosse-Wentrup, M. (2010). Closing the Sensorimotor Loop: Haptic Feedback Facilitates Decoding of Arm Movement Imagery, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (Workshop on Brain-Machine Interfaces).
  •     Bib
    Kober, J.; Mohler, B.; Peters, J. (2010). Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling, From Motor Learning to Interaction Learning in Robots, Springer Verlag.
  •     Bib
    Kober, J.; Muelling, K.; Kroemer, O.; Lampert, C.H.; Schoelkopf, B.; Peters, J. (2010). Movement Templates for Learning of Hitting and Batting, IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Kober, J.; Oztop, E.; Peters, J. (2010). Reinforcement Learning to adjust Robot Movements to New Situations, Proceedings of Robotics: Science and Systems (R:SS).
  •       Bib
    Kober, J.; Peters, J. (2010). Imitation and Reinforcement Learning - Practical Algorithms for Motor Primitive Learning in Robotics, IEEE Robotics and Automation Magazine, 17, 2, pp.55-62.
  •       Bib
    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2010). Adapting Preshaped Grasping Movements using Vision Descriptors, From Animals to Animats 11, International Conference on the Simulation of Adaptive Behavior (SAB).
  •       Bib
    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2010). Grasping with Vision Descriptors and Motor Primitives, Proceedings of the International Conference on Informatics in Control, Automation and Robotics (ICINCO).
  •       Bib
    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2010). Combining Active Learning and Reactive Control for Robot Grasping, Robotics and Autonomous Systems, 58, 9, pp.1105-1116.
  •     Bib
    Lampert, C. H.; Kroemer, O. (2010). Weakly-Paired Maximum Covariance Analysis for Multimodal Dimensionality Reduction and Transfer Learning, Proceedings of the 11th European Conference on Computer Vision (ECCV 2010).
  •     Bib
    Morimura, T.; Uchibe, E.; Yoshimoto, J.; Peters, J.; Doya, K. (2010). Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning, Neural Computation, 22, 2.
  •       Bib
    Muelling, K.; Kober, J.; Peters, J. (2010). Simulating Human Table Tennis with a Biomimetic Robot Setup, From Animals to Animats 11, International Conference on the Simulation of Adaptive Behavior (SAB).
  •       Bib
    Muelling, K.; Kober, J.; Peters, J. (2010). A Biomimetic Approach to Robot Table Tennis, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Muelling, K.; Kober, J.; Peters, J. (2010). Learning Table Tennis with a Mixture of Motor Primitives, 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2010).
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2010). Incremental Sparsification for Real-time Online Model Learning, Proceedings of Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010).
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2010). Using Model Knowledge for Learning Inverse Dynamics, IEEE International Conference on Robotics and Automation.
  •     Bib
    Nguyen Tuong, D.; Peters, J.;Seeger, M. (2010). Real-Time Local GP Model Learning, From Motor Learning to Interaction Learning in Robots, Springer Verlag, 264.
  •     Bib
    Peters, J.; Bagnell, J.A. (2010). Policy gradient methods, Encyclopedia of Machine Learning (invited article).
  •     Bib
    Peters, J.; Muelling, K.; Altun, Y. (2010). Relative Entropy Policy Search, Proceedings of the Twenty-Fourth National Conference on Artificial Intelligence (AAAI), Physically Grounded AI Track.
  •   Bib
    Peters, J.; Muelling, K.; Kober, J. (2010). Experiments with Motor Primitives to learn Table Tennis, 12th International Symposium on Experimental Robotics (ISER 2010).
  •     Bib
    Peters, J.; Tedrake, R.; Roy, N.; Morimoto, J. (2010). Robot Learning, Encyclopedia of Machine Learning.
  •     Bib
    Peters, J.;Kober, J.;Schaal, S. (2010). Policy learning algorithmis for motor learning (Algorithmen zum automatischen Erlernen von Motorfaehigkigkeiten), Automatisierungstechnik, 58, 12, pp.688-694.
  •     Bib
    Sehnke, F.; Osendorfer, C.; Rueckstiess, T.; Graves, A.; Peters, J.; Schmidhuber, J. (2010). Parameter-exploring Policy Gradients, Neural Networks, 23.
  •     Bib
    Sigaud, O.; Peters, J. (2010). From Motor Learning to Interaction Learning in Robots, Studies in Computational Intelligence, Springer Verlag, 264.
  •     Bib
    Wierstra, D.; Foerster, A.; Peters, J.; Schmidhuber, J. (2010). Recurrent Policy Gradients, Logic Journal of the IGPL, 18, pp.620-634.

2009

  •     Bib
    Chiappa, S.; Kober, J.; Peters, J. (2009). Using Bayesian Dynamical Systems for Motion Template Libraries, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
  •     Bib
    Deisenroth, M.P.; Rasmussen, C.E.; Peters, J. (2009). Gaussian Process Dynamic Programming, Neurocomputing, 72, pp.1508-1524.
  •     Bib
    Detry, R; Baseski, E.; Popovic, M.; Touati, Y.; Krueger, N; Kroemer, O.; Peters, J.; Piater, J; (2009). Learning Object-specific Grasp Affordance Densities, Proceedings of the International Conference on Development & Learning (ICDL 2009).
  •       Bib
    Gomez Rodriguez, M.; Kober, J.; Schoelkopf, B. (2009). Denoising photographs using dark frames optimized by quadratic programming, Proceedings of the First IEEE International Conference on Computational Photography (ICCP 2009).
  •     Bib
    Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J. (2009). Adaptive Importance Sampling for Value Function Approximation in Off-policy Reinforcement Learning, Neural Networks, 22, 10, pp.1399-1410.
  •     Bib
    Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J. (2009). Efficient Data Reuse in Value Function Approximation, Proceedings of the 2009 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
  •     Bib
    Hachiya, H.; Peters, J.; Sugiyama, M. (2009). Efficient Sample Reuse in EM-based Policy Search, Proceedings of the 16th European Conference on Machine Learning (ECML 2009).
  •     Bib
    Hoffman, M.; de Freitas, N. ; Doucet, A.; Peters, J. (2009). An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward, Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AIStats).
  •     Bib
    Kober, J.; Peters, J. (2009). Learning new basic Movements for Robotics, Proceedings of Autonome Mobile Systeme (AMS 2009).
  •     Bib
    Kober, J.; Peters, J. (2009). Policy Search for Motor Primitives in Robotics, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
  •     Bib
    Kober, J.; Peters, J. (2009). Learning Motor Primitives for Robotics, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Kober, J.; Peters, J. (2009). Reinforcement Learning fuer Motor-Primitive, Kuenstliche Intelligenz.
  •     Bib
    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2009). Active Learning Using Mean Shift Optimization for Robot Grasping, Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009).
  •     Bib
    Lampert, C.H.; Peters, J. (2009). Active Structured Learning for High-Speed Object Detection, Proceedings of the DAGM (Pattern Recognition).
  •     Bib
    Muelling, K.; Peters, J. (2009). A computational model of human table tennis for robot application, Proceedings of Autonome Mobile Systeme (AMS 2009).
  •     Bib
    Neumann, G.; Maass, W; Peters, J. (2009). Learning Complex Motions by Sequencing Simpler Motion Templates, Proceedings of the International Conference on Machine Learning (ICML2009).
  •     Bib
    Neumann, G.; Peters, J. (2009). Fitted Q-iteration by Advantage Weighted Regression, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
  •     Bib
    Nguyen Tuong, D.; Seeger, M.; Peters, J. (2009). Local Gaussian Process Regression for Real Time Online Model Learning and Control, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
  •     Bib
    Nguyen Tuong, D.; Seeger, M.; Peters, J. (2009). Sparse Online Model Learning for Robot Control with Support Vector Regression, Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009).
  •     Bib
    Nguyen Tuong, D.; Seeger, M.; Peters, J. (2009). Model Learning with Local Gaussian Process Regression, Advanced Robotics, 23, 15, pp.2015-2034.
  •     Bib
    Peters, J.; Kober, J. (2009). Using Reward-Weighted Imitation for Robot Reinforcement Learning, Proceedings of the 2009 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
  •     Bib
    Peters, J.; Kober, J.; Muelling, K.; Nguyen-Tuong, D.; Kroemer, O. (2009). Towards Motor Skill Learning for Robotics, Proceedings of the International Symposium on Robotics Research (ISRR), Invited Paper.
  •     Bib
    Peters, J.; Morimoto, J.; Tedrake, R.; Roy, N. (2009). Robot Learning, IEEE Robotics & Automation Magazine, 16, 3, pp.19-20.
  •     Bib
    Peters, J.; Ng, A. (2009). Guest Editorial: Special Issue on Robot Learning, Part B, Autonomous Robots (AURO), 27, 2.
  •     Bib
    Peters, J.; Ng, A. (2009). Guest Editorial: Special Issue on Robot Learning, Part A, Autonomous Robots (AURO), 27, 1.
  •     Bib
    Piater, J.; Jodogne, S.; Detry, R.; Kraft, D.; Krueger, N.; Kroemer, O.; Peters, J. (2009). Learning Visual Representations for Interactive Systems, Proceedings of the International Symposium on Robotics Research (ISRR), Invited Paper.
  •     Bib
    Sigaud, O.; Peters, J. (2009). From Motor Learning to Interaction Learning in Robots, Proceedings of Journees Nationales de la Recherche en Robotique.

2008

  •     Bib
    Deisenroth, M.P.; Peters, J.; Rasmussen, C.E. (2008). Approximate Dynamic Programming with Gaussian Processes, American Control Conference.
  •     Bib
    Deisenroth, M.P.; Rasmussen, C.E.; Peters, J. (2008). Model-Based Reinforcement Learning with Continuous States and Actions, Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2008), pp.19-24.
  •     Bib
    Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J. (2008). Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation, Proceedings of the Twenty-Third National Conference on Artificial Intelligence (AAAI 2008).
  •       Bib
    Kober, J. (2008). Reinforcement Learning for Motor Primitives, Dipl-Ing Thesis, University of Stuttgart.
  •     Bib
    Kober, J.; Mohler, B.; Peters, J. (2008). Learning Perceptual Coupling for Motor Primitives, International Conference on Intelligent Robot Systems (IROS).
  •   Bib
    Kober, J.; Peters, J. (2008). Reinforcement Learning of Perceptual Coupling for Motor Primitives, Proceedings of the European Workshop on Reinforcement Learning (EWRL).
  •   Bib
    Lesperance, Y.; Lakemeyer, G.; Peters, J.; Pirri, F. (2008). Proceedings of the 6th International Cognitive Robotics Workshop (CogRob 2008), July 21-22, 2008, Patras, Greece, ISBN 978-960-6843-09-9.
  •     Bib
    Nakanishi, J.;Cory, R.;Mistry, M.;Peters, J.;Schaal, S. (2008). Operational space control: A theoretical and empirical comparison, International Journal of Robotics Research (IJRR), 27, 6, pp.737-757.
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2008). Learning Inverse Dynamics: a Comparison, Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2008).
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2008). Local Gaussian Processes Regression for Real-time Model-based Robot Control, International Conference on Intelligent Robot Systems (IROS).
  •     Bib
    Nguyen Tuong, D.; Peters, J.; Seeger, M.; Schoelkopf, B. (2008). Learning Robot Dynamics for Computed Torque Control using Local Gaussian Processes Regression, Proceedings of the ECSIS Symposium on Learning and Adaptive Behavior in Robotic Systems, LAB-RS 2008.
  •     Bib
    Peters, J. (2008). Machine Learning for Robotics, VDM-Verlag, ISBN 978-3-639-02110-3.
  •     Bib
    Peters, J. (2008). Machine Learning for Motor Skills in Robotics, Kuenstliche Intelligenz, 3.
  •     Bib
    Peters, J.; Kober, J.; Nguyen-Tuong, D. (2008). Policy Learning - a unified perspective with applications in robotics, Proceedings of the European Workshop on Reinforcement Learning (EWRL).
  •     Bib
    Peters, J.; Nguyen-Tuong, D. (2008). Real-Time Learning of Resolved Velocity Control on a Mitsubishi PA-10, International Conference on Robotics and Automation (ICRA).
  •     Bib
    Peters, J.; Schaal, S. (2008). Natural actor critic, Neurocomputing, 71, 7-9, pp.1180-1190.
  •     Bib
    Peters, J.; Schaal, S. (2008). Learning to control in operational space, International Journal of Robotics Research (IJRR), 27, pp.197-212.
  •     Bib
    Peters, J.; Schaal, S. (2008). Reinforcement learning of motor skills with policy gradients, Neural Networks, 21, 4, pp.682-97.
  •     Bib
    Peters, J.; Seeger, M. (2008). Computed Torque Control with Nonparametric Regressions Techniques, American Control Conference.
  •     Bib
    Peters, J.;Mistry, M.;Udwadia, F. E.;Nakanishi, J.;Schaal, S. (2008). A unifying framework for robot control with redundant DOFs, Autonomous Robots (AURO), 24, 1, pp.1-12.
  •     Bib
    Sehnke, F.; Osendorfer, C; Rueckstiess, T; Graves, A.; Peters, J.; Schmidhuber, J. (2008). Policy Gradients with Parameter-based Exploration for Control, Proceedings of the International Conference on Artificial Neural Networks (ICANN).
  •     Bib
    Steinke, F.; Hein, M.; Peters, J.; Schoelkopf, B (2008). Manifold-valued Thin-Plate Splines with Applications in Computer Graphics, Computer Graphics Forum (Special Issue on Eurographics 2008), 27, 2.
  •     Bib
    Wierstra, D.; Schaul, T.; Peters, J.; Schmidthuber, J. (2008). Fitness Expectation Maximization, 10th International Conference on Parallel Problem Solving from Nature (PPSN 2008).
  •     Bib
    Wierstra, D.; Schaul, T.; Peters, J.; Schmidhuber, J. (2008). Natural Evolution Strategies, 2008 IEEE Congress on Evolutionary Computation.
  •     Bib
    Wierstra, D.; Schaul,T.; Peters, J.; Schmidhuber, J. (2008). Episodic Reinforcement Learning by Logistic Reward-Weighted Regression, Proceedings of the International Conference on Artificial Neural Networks (ICANN).

2007

  •     Bib
    Nakanishi, J.; Mistry, M.; Peters, J.; Schaal, S. (2007). Experimental evaluation of task space position/orientation control towards compliant control for humanoid robots, IEEE International Conference on Intelligent Robotics Systems (IROS 2007).
  •   Bib
    Peters, J. (2007). Computational Intelligence: By Amit Konar, The Computer Journal, 50, 6, pp.758.
  •   Bib
    Peters, J. (2007). Machine Learning of Motor Skills for Robotics, Ph.D. Thesis, Department of Computer Science, University of Southern California.
  •     Bib
    Peters, J. (2007). Relative Entropy Policy Search, CLMC Technical Report: TR-CLMC-2007-2, University of Southern California.
  •     Bib
    Peters, J.; Schaal, S. (2007). Policy Learning for Motor Skills, Proceedings of 14th International Conference on Neural Information Processing (ICONIP).
  •     Bib
    Peters, J.; Schaal, S. (2007). Reinforcement learning for operational space control, International Conference on Robotics and Automation (ICRA2007).
  •     Bib
    Peters, J.; Schaal, S. (2007). Applying the episodic natural actor-critic architecture to motor primitive learning, Proceedings of the 2007 European Symposium on Artificial Neural Networks (ESANN).
  •     Bib
    Peters, J.; Schaal, S.; Schoelkopf, B. (2007). Towards Machine Learning of Motor Skills, Proceedings of Autonome Mobile Systeme (AMS).
  •     Bib
    Peters, J.;Schaal, S. (2007). Using reward-weighted regression for reinforcement learning of task space control, Proceedings of the 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
  •     Bib
    Peters, J.;Schaal, S. (2007). Reinforcement learning by reward-weighted regression for operational space control, Proceedings of the International Conference on Machine Learning (ICML2007).
  •   Bib
    Peters, J.;Theodorou, E.;Schaal, S. (2007). Policy gradient methods for machine learning, INFORMS Conference of the Applied Probability Society.
  •     Bib
    Riedmiller, M.;Peters, J.;Schaal, S. (2007). Evaluation of policy gradient methods and variants on the cart-pole benchmark, Proceedings of the 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
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    Theodorou, E; Peters, J.; Schaal, S. (2007). Reinforcement Learning for Optimal Control of Arm Movements, Abstracts of the 37st Meeting of the Society of Neuroscience.
  •     Bib
    Wierstra, D.; Foerster, A.; Peters, J.; Schmidhuber, J. (2007). Solving Deep Memory POMDPs with Recurrent Policy Gradients, Proceedings of the International Conference on Artificial Neural Networks (ICANN).

2006

  •     Bib
    Peters, J.;Schaal, S. (2006). Learning operational space control, Robotics: Science and Systems (RSS 2006), Cambridge, MA: MIT Press.
  •     Bib
    Peters, J.;Schaal, S. (2006). Reinforcement Learning for Parameterized Motor Primitives, Proceedings of the 2006 International Joint Conference on Neural Networks (IJCNN).
  •     Bib
    Peters, J.;Schaal, S. (2006). Policy gradient methods for robotics, Proceedings of the IEEE International Conference on Intelligent Robotics Systems (IROS 2006).
  •     Bib
    Ting, J.;Mistry, M.;Nakanishi, J.;Peters, J.;Schaal, S. (2006). A Bayesian approach to nonlinear parameter identification for rigid body dynamics, Robotics: Science and Systems (RSS 2006), Cambridge, MA: MIT Press.

2005

  •     Bib
    Nakanishi, J.;Cory, R.;Mistry, M.;Peters, J.;Schaal, S. (2005). Comparative experiments on task space control with redundancy resolution, IEEE International Conference on Intelligent Robots and Systems (IROS 2005).
  •     Bib
    Peters, J.;Mistry, M.;Udwadia, F. E.;Cory, R.;Nakanishi, J.;Schaal, S. (2005). A unifying framework for the control of robotics systems, IEEE International Conference on Intelligent Robots and Systems (IROS 2005).
  •     Bib
    Peters, J.;Mistry, M.;Udwadia, F. E.;Schaal, S. (2005). A new methodology for robot control design, The 5th ASME International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC 2005).
  •     Bib
    Peters, J.;Vijayakumar, S.;Schaal, S. (2005). Natural Actor-Critic, Proceedings of the 16th European Conference on Machine Learning (ECML 2005).

2004

  •   Bib
    Peters, J.; Schaal, S. (2004). Learning Motor Primitives with Reinforcement Learning, Proceedings of the 11th Joint Symposium on Neural Computation.
  •     Bib
    Schaal, S.;Peters, J.;Nakanishi, J.;Ijspeert, A. (2004). Learning Movement Primitives, International Symposium on Robotics Research (ISRR2003).

2003

  •     Bib
    Mohajerian, P.;Peters, J.;Ijspeert, A.;Schaal, S. (2003). A unifying computational framework for optimization and dynamic systems approaches to motor control, Proceedings of the 10th Joint Symposium on Neural Computation (JSNC 2003).
  •     Bib
    Peters, J.;Vijayakumar, S.;Schaal, S. (2003). Reinforcement learning for humanoid robotics, IEEE-RAS International Conference on Humanoid Robots (Humanoids2003).
  •     Bib
    Peters, J.;Vijayakumar, S.;Schaal, S. (2003). Scaling reinforcement learning paradigms for motor learning, Proceedings of the 10th Joint Symposium on Neural Computation (JSNC 2003).
  •     Bib
    Schaal, S.;Peters, J.;Nakanishi, J.;Ijspeert, A. (2003). Control, planning, learning, and imitation with dynamic movement primitives, Workshop on Bilateral Paradigms on Humans and Humanoids, IEEE International Conference on Intelligent Robots and Systems (IROS 2003).

2002

  •     Bib
    Peters, J. (2002). Policy Gradient Methods for Control Applications, CLMC Technical Report: TR-CLMC-2007-1, University of Southern California.
  •   Bib
    Vijayakumar, S.; D’Souza, A.; Peters, J.; Conradt, J.; Rutkowski,T.; Ijspeert, A.; Nakanishi, J.; Inoue, M.; Shibata, T.; Wiryo, A.; Itti, L.; Amari, S.; Schaal, S (2002). Real-Time Statistical Learning for Oculomotor Control and Visuomotor Coordination, Advances in Neural Information Processing Systems (NIPS/NeurIPS), Demonstration Track.

2001

  •       Bib
    Burdet, E.; Tee, K.P.; Chew, C.M.; Peters, J.; Bt, V.L. (2001). Hybrid IDM/Impedance Learning in Human Movements, First International Symposium on Measurement, Analysis and Modeling of Human Functions Proceedings.

2000

  •       Bib
    Peters, J.; Riener, R (2000). A real-time model of the human knee for application in virtual orthopaedic trainer, Proceedings of the 10th International Conference on Biomedical Engineering Conference (ICBME).

1998

  •   Bib
    Peters, J. (1998). Fuzzy Logic for Practical Applications, Kuenstliche Intelligenz (KI), 4, pp.60.