This list is automatically created, please see publications by year in order to have a more chronological overview on my publications. Note that the list on this page is automatically generated and as such always overlapping due to overlapping keywords.

Reinforcement Learning

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.
[Keywords: off-policy reinforcement learning; value function approximation; policy iteration; adaptive importance sampling; importance-weighted cross-validation; efficient sample reuse]
[Details]

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).
[Keywords: reinforcement learning, policy gradient, weighted regression]
[Details] [PDF]

Peters, J.;Schaal, S. (2008). Natural actor critic, Neurocomputing, 71, 7-9, pp.1180-1190.
[Keywords: reinforcement learning, policy gradient, natural actor-critic, natural gradients]
[Details] [PDF]

Peters, J.;Schaal, S. (2008). Learning to control in operational space, International Journal of Robotics Research, 27, pp.197-212.
[Keywords: operational space control, learning, EM ALGORITHM, redundancy resolution, reinforcement learning]
[Details] [PDF]

Peters, J.;Schaal, S. (2008). Reinforcement learning of motor skills with policy gradients, Neural Networks, 21, 4, pp.682-97.
[Keywords: Reinforcement learning, Policy gradient methods, Natural gradients, Natural Actor-Critic, Motor skills, Motor primitives]
[Details] [PDF]

Peters, J., Schaal, S. (2007). Policy Learning for Motor Skills, Proceedings of 14th International Conference on Neural Information Processing (ICONIP).
[Keywords: Machine Learning, Reinforcement Learning, Robotics, Motor Primitives, Policy Gradients, Natural Actor-Critic, Reward-Weighted Regression]
[Details] [PDF]

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).
[Keywords: policy gradients, reinforcement learning]
[Details] [PDF]

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..
[Keywords: Optimal Control,Reinforcement Learning, Arm Movements]
[Details]

Peters, J. (2007). Machine Learning of Motor Skills for Robotics, Ph.D. Thesis, Department of Computer Science, University of Southern California.
[Keywords: Machine Learning, Reinforcement Learning, Robotics, Motor Primitives, Policy Gradients, Natural Actor-Critic, Reward-Weighted Regression]
[Details]

Peters, J.;Schaal, S. (2007). Reinforcement learning for operational space control, International Conference on Robotics and Automation (ICRA2007), pp.2111-2116.
[Keywords: operational space control, reinforcement learning, weighted regression, EM-Algorithm]
[Details] [PDF]

Peters, J.;Schaal, S. (2007). Using reward-weighted regression for reinforcement learning of task space control, Proceedings of the 2007 IEEE Internatinal Symposium on Approximate Dynamic Programming and Reinforcement Learning.
[Keywords: reinforcement learning, cart-pole, policy gradient methods]
[Details] [PDF]

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).
[Keywords: reinforcement learning, policy gradient methods, motor primitives, natural actor-critic]
[Details] [PDF]

Peters, J.;Schaal, S. (2007). Reinforcement learning by reward-weighted regression for operational space control, Proceedings of the International Conference on Machine Learning (ICML2007).
[Keywords: reinforcement learning, operational space control, weighted regression]
[Details] [PDF]

Peters, J.;Theodorou, E.;Schaal, S. (2007). Policy gradient methods for machine learning, INFORMS Conference of the Applied Probability Society.
[Keywords: policy gradient methods, reinforcement learning, simulation-optimization]
[Details]

Riedmiller, M.;Peters, J.;Schaal, S. (2007). Evaluation of policy gradient methods and variants on the cart-pole benchmark, Proceedings of the 2007 IEEE Internatinal Symposium on Approximate Dynamic Programming and Reinforcement Learning.
[Keywords: reinforcement learning, cart-pole, policy gradient methods]
[Details] [PDF]

Peters, J.;Schaal, S. (2006). Reinforcement Learning for Parameterized Motor Primitives, Proceedings of the 2006 International Joint Conference on Neural Networks (IJCNN 2006).
[Keywords: motor primitives, reinforcement learning]
[Details] [PDF]

Peters, J.;Schaal, S. (2006). Policy gradient methods for robotics, Proceedings of the IEEE International Conference on Intelligent Robotics Systems (IROS 2006).
[Keywords: policy gradient methods, reinforcement learning, robotics]
[Details] [PDF]

Peters, J.;Vijayakumar, S.;Schaal, S. (2005). Natural Actor-Critic, in: Gama, J.;Camacho, R.;Brazdil, P.;Jorge, A.;Torgo, L. (eds.), Proceedings of the 16th European Conference on Machine Learning (ECML 2005), 3720, pp.280-291, Springer.
[Keywords: Reinforcement Learning, Policy Gradients, Natural Gradients]
[Details] [PDF]

Peters, J.;Vijayakumar, S.;Schaal, S. (2003). Reinforcement learning for humanoid robotics, Humanoids2003, Third IEEE-RAS International Conference on Humanoid Robots.
[Keywords: reinforcement learning, policy gradients, movement primitives, behaviors, dynamic systems, humanoid robotics]
[Details] [PDF]

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).
[Keywords: Reinforcement learning, neurodynamic programming, actorcritic methods, policy gradient methods, natural policy gradient]
[Details] [PDF]

Kwee, I.;Hutter, M.;Schmidhuber, J. (2001). Gradient-based reinforcement planning in policy-search methods, IDSIA.
[Keywords: reinforcement learning policy gradients model-based]
[Details] [PDF]

Control

Nakanishi, J.;Cory, R.;Mistry, M.;Peters, J.;Schaal, S. (2008). Operational space control: A theoretical and emprical comparison, International Journal of Robotics Research, 27, 6, pp.737-757.
[Keywords: task space control, operational space control, redundancy resolution, humanoid robotics]
[Details] [PDF]

Peters, J. (2008). Machine Learning for Motor Skills in Robotics, Künstliche Intelligenz, 3.
[Keywords: motor control, motor primitives, motor learning]
[Details] [PDF]

Peters, J.;Schaal, S. (2008). Learning to control in operational space, International Journal of Robotics Research, 27, pp.197-212.
[Keywords: operational space control, learning, EM ALGORITHM, redundancy resolution, reinforcement learning]
[Details] [PDF]

Peters, J.;Mistry, M.;Udwadia, F. E.;Nakanishi, J.;Schaal, S. (2008). A unifying methodology for robot control with redundant DOFs, Autonomous Robots, 24, 1, pp.1-12.
[Keywords: operational space control, inverse control, dexterous manipulation, optimal control]
[Details] [PDF]

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..
[Keywords: Optimal Control,Reinforcement Learning, Arm Movements]
[Details]

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).
[Keywords: operational space control, quaternion, task space control, resolved motion rate control, resolved acceleration, force control]
[Details] [PDF]

Peters, J.;Schaal, S. (2007). Reinforcement learning for operational space control, International Conference on Robotics and Automation (ICRA2007), pp.2111-2116.
[Keywords: operational space control, reinforcement learning, weighted regression, EM-Algorithm]
[Details] [PDF]

Peters, J.;Schaal, S. (2007). Reinforcement learning by reward-weighted regression for operational space control, Proceedings of the International Conference on Machine Learning (ICML2007).
[Keywords: reinforcement learning, operational space control, weighted regression]
[Details] [PDF]

Peters, J.;Schaal, S. (2006). Learning operational space control, in: Burgard, W.;Sukhatme, G. S.;Schaal, S. (eds.), Robotics: Science and Systems (RSS 2006), Cambridge, MA: MIT Press.
[Keywords: operational space control redundancy forward models inverse models compliance reinforcement leanring locally weighted learning]
[Details] [PDF]

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), pp.3901-3908.
[Keywords: manipulator dynamics redundant manipulators space optimization dynamical decoupling humanoid robots inverse kinematics motor coordination redundancy resolution robot dynamics seven-degree-of-freedom anthropomorphic robot arm task space control Dynamical d]
[Details] [PDF]

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).
[Keywords: robot control, nonlinear control, gauss principle]
[Details] [PDF]

Udwadia, F. E.;Weber, H.;Leitmann, G. (2004). Dynamical systems and control, Stability and control ; v. 22, pp.ix, 437 p., CRC Press.
[Keywords: Dynamics. Differentiable dynamical systems. Control theory.]
[Details]

Mohajerian, P.;Peters, J.;Ijspeert, A.;Schaal, S. (2003). A unifying computational framework for optimization and dynamic systemsapproaches to motor control, Proceedings of the 10th Joint Symposium on Neural Computation (JSNC 2003).
[Keywords: computational motor control, optimization, dynamic systems, formal modeling]
[Details] [PDF]

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.
[Keywords: human motor control]
[Details]

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).
[Keywords: Biomechanics, human motor control]
[Details]

Hess, G.;Donoghue, J. P. (1994). Long-term potentiation of horizontal connections provides a mechanism to reorganize cortical motor maps, Journal of Neurophysiology, 71, 6, pp.2543-2547.
[Keywords: reorganization,motor cortex,plasticity,MI,motor control,]
[Details]

Learning Motor Primitives

Peters, J. (2008). Machine Learning for Motor Skills in Robotics, Künstliche Intelligenz, 3.
[Keywords: motor control, motor primitives, motor learning]
[Details] [PDF]

Peters, J.;Schaal, S. (2008). Reinforcement learning of motor skills with policy gradients, Neural Networks, 21, 4, pp.682-97.
[Keywords: Reinforcement learning, Policy gradient methods, Natural gradients, Natural Actor-Critic, Motor skills, Motor primitives]
[Details] [PDF]

Peters, J., Schaal, S. (2007). Policy Learning for Motor Skills, Proceedings of 14th International Conference on Neural Information Processing (ICONIP).
[Keywords: Machine Learning, Reinforcement Learning, Robotics, Motor Primitives, Policy Gradients, Natural Actor-Critic, Reward-Weighted Regression]
[Details] [PDF]

Peters, J. (2007). Machine Learning of Motor Skills for Robotics, Ph.D. Thesis, Department of Computer Science, University of Southern California.
[Keywords: Machine Learning, Reinforcement Learning, Robotics, Motor Primitives, Policy Gradients, Natural Actor-Critic, Reward-Weighted Regression]
[Details]

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).
[Keywords: reinforcement learning, policy gradient methods, motor primitives, natural actor-critic]
[Details] [PDF]

Peters, J.;Schaal, S. (2006). Reinforcement Learning for Parameterized Motor Primitives, Proceedings of the 2006 International Joint Conference on Neural Networks (IJCNN 2006).
[Keywords: motor primitives, reinforcement learning]
[Details] [PDF]

Peters, J., Schaal, S. (2004). Learning Motor Primitives with Reinforcement Learning, Proceedings of the 11th Joint Symposium on Neural Computation.
[Keywords: natural policy gradients, motor primitives, natural actor-critic]
[Details]

Robotics

Peters, J.; Morimoto, J.; Tedrake, R.; Roy, N. (2009). Robot Learning, IEEE Robotics & Automation Magazine, 16, 3, pp.19-20.
[Keywords: robot learning, tc spotlight]
[Details]

Nakanishi, J.;Cory, R.;Mistry, M.;Peters, J.;Schaal, S. (2008). Operational space control: A theoretical and emprical comparison, International Journal of Robotics Research, 27, 6, pp.737-757.
[Keywords: task space control, operational space control, redundancy resolution, humanoid robotics]
[Details] [PDF]

Peters, J., Schaal, S. (2007). Policy Learning for Motor Skills, Proceedings of 14th International Conference on Neural Information Processing (ICONIP).
[Keywords: Machine Learning, Reinforcement Learning, Robotics, Motor Primitives, Policy Gradients, Natural Actor-Critic, Reward-Weighted Regression]
[Details] [PDF]

Peters, J.; Schaal, S.; Schoelkopf, B. (2007). Towards Machine Learning of Motor Skills, Proceedings of Autonome Mobile Systeme (AMS).
[Keywords: Motor Skill Learning, Robotics, Natural Actor-Critic, Reward-Weighted Regeression]
[Details] [PDF]

Peters, J. (2007). Machine Learning of Motor Skills for Robotics, Ph.D. Thesis, Department of Computer Science, University of Southern California.
[Keywords: Machine Learning, Reinforcement Learning, Robotics, Motor Primitives, Policy Gradients, Natural Actor-Critic, Reward-Weighted Regression]
[Details]

Peters, J.;Schaal, S. (2006). Policy gradient methods for robotics, Proceedings of the IEEE International Conference on Intelligent Robotics Systems (IROS 2006).
[Keywords: policy gradient methods, reinforcement learning, robotics]
[Details] [PDF]

Jansen, B.;Belpaeme, T. (2006). A computational model of intention reading in imitation, ROBOTICS AND AUTONOMOUS SYSTEMS, 54, 5, pp.394-402, ELSEVIER SCIENCE BV.
[Keywords: imitation imitation on robots goal-directed imitation intention]
[Details]

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), pp.3901-3908.
[Keywords: manipulator dynamics redundant manipulators space optimization dynamical decoupling humanoid robots inverse kinematics motor coordination redundancy resolution robot dynamics seven-degree-of-freedom anthropomorphic robot arm task space control Dynamical d]
[Details] [PDF]

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).
[Keywords: robot control, nonlinear control, gauss principle]
[Details] [PDF]

Peters, J.;Vijayakumar, S.;Schaal, S. (2003). Reinforcement learning for humanoid robotics, Humanoids2003, Third IEEE-RAS International Conference on Humanoid Robots.
[Keywords: reinforcement learning, policy gradients, movement primitives, behaviors, dynamic systems, humanoid robotics]
[Details] [PDF]

Human Motor Control

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.
[Keywords: human motor control]
[Details]

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).
[Keywords: Biomechanics, human motor control]
[Details]

Book Reviews

Peters, J. (2007). Computational Intelligence: By Amit Konar, The Computer Journal, 50, 6, pp.758.
[Keywords: book review]
[Details]

Peters, J. (1998). Fuzzy Logic for Practical Applications, Kuenstliche Intelligenz (KI), 4, pp.60.
[Keywords: book review]
[Details]

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