Stefan Schaal is an Associate Professor in Computer Science, Neuroscience, and Biomedical Engineering at the University of Southern California, and an Invited Researcher at the ATR Computational Neuroscience Laboratory in Japan, where he held an appointment as Head of the Computational Learning Group during an international ERATO project, the Kawato Dynamic Brain Project (ERATO/JST). Before joining USC, Dr. Schaal was a postdoctoral fellow at the Department of Brain and Cognitive Sciences and the Artificial Intelligence Laboratory at MIT, an Invited Researcher at the ATR Human Information Processing Research Laboratories in Japan, and an Adjunct Assistant Professor at the Georgia Institute of Technology and at the Department of Kinesiology of the Pennsylvania State University.

Dr. Schaal's research interests include topics of statistical and machine learning, neural networks, computational neuroscience, functional brain imaging, nonlinear dynamics, nonlinear control theory, and biomimetic robotics. He applies his research to problems of artificial and biological motor control and motor learning, focusing on both theoretical investigations and experiments with human subjects and anthropomorphic robot equipment.

Dr. Schaal has co-authored over 200 papers in refereed journals and conferences. He is a co-founder of the "IEEE/RAS International Conference and Humanoid Robotics", and a co-founder of "Robotics Science and Systems", a highly selective new conference featuring the best work in robotics every year. Dr. Schaal served as Program Chair at these conferences and he was the Program Chair of "Simulated and Adaptive Behavior" (SAB 2004) and the "IEEE/RAS International Conference on Robotics and Automation" (ICRA 2008), the largest robotics conference in the world. Dr. Schaal is has also been an Area Chair at "Neural Information Processing Systems" (NIPS) and served as Program Committee Member of the "International Conference on Machine Learning" (ICML). Dr. Schaal serves on the editorial board of the journals "Neural Networks", "International Journal of Humanoid Robotics", and "Frontiers in Neurorobotics". Dr. Schaal is a member of the German National Academic Foundation (Studienstiftung des Deutschen Volkes), the Alexander von Humboldt Foundation, the Society For Neuroscience, the Society for Neural Control of Movement, the IEEE, and AAAS.

Address:
Dr. Stefan Schaal
University of Southern California
Hedco Neurosciences Building, HNB-103
3641 Watt Way
Los Angeles, CA 90089-2520, USA

Email:

Phone:
(213) 740 9418

Fax:
(213) 740 1510

Publications:

Evangelos A. Theodorou, Jonas Buchli, Stefan Schaal (submitted). Reinforcement Learning of Motor Skills in High Dimensions: A Pah Integral Approach. (MANUSCRIPT UNDER REVIEW. SUGGESTIONS WELCOME)).
[Keywords: reinforcement learning, stochastic optimal control]
[Detail] [BibTeX] [PDF]

Edakunni, N. U.;Schaal, S.;Vijayakumar, S. (submitted). Probabilistic incremental locally weighted learning using randomly varying coefficient model, Machine Learning.
[Keywords: locally weighted learning, bayesian regression, bandwidth adaptation, variational methods, online learning]
[Detail] [BibTeX]

Ting, J.;D'Souza, A.;Schaal, S. (submitted). A Bayesian approach to nonlinear parameter identification for rigid-body dynamics, Neural Networks.
[Detail] [BibTeX]

Mohajerian, P.;Mistry, M.;Schaal, S. (submitted). Cerebral or spinal level interaction of rhythmic and discrete movements during two-joint arm task, Journal of Neurophysiology.
[Detail] [BibTeX]

Ijspeert, A.;Nakanishi, J.;Schaal, S. (submitted). Learning nonlinear dynamical systems, Neural Computation.
[Detail] [BibTeX]

Evangelos A. Theodorou, Jonas Buchli, Stefan Schaal (submitted). Learning Policy Improvements with Path Integrals.
[Detail] [BibTeX]

Ting, J.;D'Souza, A.;Schaal, S. (in press). Efficient learning and feature detection in high dimensional spaces, Neural Computation.
[Keywords: high-dimensional regression, feature selection, generalized linear models, variational bayesian methods, sparse bayesian learning]
[Detail] [BibTeX] [PDF]

Hoffmann, H.;Schaal, S.;Vijayakumar, S. (2009). Local dimensionality reduction for non-parametric regression, Neural Processing Letters.
[Keywords: locally weighted learning, dimensionality reduction,correlation, dimensionality reduction, factor analysis, incremental learning, kernel function, locally-weighted regression, partial least squares, principal component analysis, principal component regres]
[Detail] [BibTeX] [PDF]

Hoffmann, H.;Pastor, P.;Park, D.-H.;Schaal, S. (2009). Biologically-inspired dynamical systems for movement generation: automatic real-time goal adaptation and obstacle avoidance, International Conference on Robotics and Automation (ICRA2009).
[Keywords: movement primitives, dynamic systems, obstacle avoidance, generalization]
[Detail] [BibTeX] [PDF]

Evangelos A. Theodorou.;Buchli, J.;Schaal, S. (2009). Path integral stochastic optimal control for rigid body dynamics, IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL2009).
[Keywords: reinforcement learning, optimal control, path integrals, stochastic systems]
[Detail] [BibTeX] [PDF]

Schaal, S. (2009). The SL simulation and real-time control software package, University of Southern California.
[Keywords: simulation environment, documentation, real-time control envirionment, motor control]
[Detail] [BibTeX] [PDF]

Pastor, P.;Hoffmann, H.;Asfour, T.;Schaal, S. (2009). Learning and generalization of motor skills by learning from demonstration, International Conference on Robotics and Automation (ICRA2009).
[Keywords: movement primitives, dynamic systems, obstacle avoidance, generalization, affordances]
[Detail] [BibTeX] [PDF]

Hoffmann, H.;Theodorou, E.;Schaal, S. (2009). Human optimization strategies under reward feedback, Abstracts of Neural Control of Movement Conference (NCM 2009).
[Keywords: computational motor control, reinforcement leanring, human subjects]
[Detail] [BibTeX]

Kalakrishnan, M.; Buchli, J.; Pastor, P.; Schaal, S. (2009). Learning Locomotion over Rough Terrain using Terrain Templates, IEEE/RSJ International Conference on Intelligent RObots and Systems.
[Keywords: quadruped locomotion, learning from demonstration]
[Detail] [BibTeX] [PDF]

Buchli, J.; Kalakrishnan, M.; Mistry, M.; Pastor, P.; Schaal, S. (2009). Compliant Quadruped Locomotion Over Rough Terrain, IEEE/RSJ International Conference on Intelligent RObots and Systems.
[Keywords: quadruped locomotion, inverse dynamics, force control]
[Detail] [BibTeX] [PDF]

Ting, J. A.;D'Souza, A.;Yamamoto, K.;Yoshioka, T.;Hoffman, D.;Kakei, S.;Sergio, L.;Kalaska, J.;Kawato, M.;Strick, P.;Schaal, S. (2008). Variational Bayesian least squares: an application to brain-machine interface data, Neural Netw, 21, 8, pp.1112-31.
[Keywords: motor control, computational neuroscience, emg reconstruction, motor cortex, brain machine interfaces, bayesian least squares]
[Detail] [BibTeX] [PDF]

Ting, J.;Kalakrishnan, M.;Vijayakumar, S.;Schaal, S. (2008). Bayesian kernel shaping for learning control, in: Koller, D.;Bengio, Y.;Schuurmans, D.;Bottou, L.;Culotta, A. (eds.), Advances in Neural Information Processing Systems 21 (NIPS 2008), Cambridge, MA: MIT Press.
[Keywords: locally weighted learning, kernel regression, bayesian learning, nonstationary processes]
[Detail] [BibTeX] [PDF]

Tevatia, G.;Schaal, S. (2008). Efficient inverse kinematics algorithms for highdimensional movement systems, CLMC Technical Report: TR-CLMC-2008-1.
[Keywords: inverse kinematics, extended jacobian]
[Detail] [BibTeX] [PDF]

Theodorou, E.;Hoffmann, H.;Mistry, M.;Schaal, S. (2008). Computational model for movement learning under uncertain cost, Abstracts of the Society of Neuroscience Meeting (SFN 2008).
[Keywords: computational motor control, motor planning, optimization, reinforcement learning]
[Detail] [BibTeX]

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]
[Detail] [BibTeX] [PDF]

Mistry, M.;Theodorou, E.;Hoffmann, H.;Schaal, S. (2008). The dual role of uncertainty in force field learning, Abstracts of the Eighteenth Annual Meeting of Neural Control of Movement (NCM).
[Keywords: computational motor control, optimal control, redundancy resolution, internal model]
[Detail] [BibTeX]

Hoffmann, H.;Theodorou, E.;Schaal, S. (2008). Behavioral experiments on reinforcement learning in human motor control, Abstracts of the Eighteenth Annual Meeting of Neural Control of Movement (NCM).
[Keywords: computational motor control, optimal control, reinforcement learning]
[Detail] [BibTeX]

Heiko Hoffmann, Evangelos Theodorou, and Stefan Schaal (2008). Optimization strategies in human reinforcement learning, Advances in Computational Motor Control VII, Symposium at the Society for Neuroscience Meeting, Washington DC, 2008.
[Keywords: reinforcement learning, motor control, psychophysics]
[Detail] [BibTeX] [PDF]

M. Mistry, E. A.Theodorou, G. Liaw, T. Yoshioka, S. Schaal, M. Kawato (2008). Adaptation to a sub-optimal desired trajectory, Advances in Computational Motor Control VII, Symposium at the Society for Neuroscience Meeting, Washington DC, 2008.
[Detail] [BibTeX] [PDF]

Dae-Hyung Park, Heiko Hoffmann, Peter Pastor, and Stefan Schaal (2008). Movement reproduction and obstacle avoidance with dynamic movement primitives and potential fields, IEEE International Conference on Humanoid Robots, 2008..
[Detail] [BibTeX] [PDF]

Heiko Hoffmann, Peter Pastor, and Stefan Schaal (2008). Dynamic movement primitives for movement generation motivated by convergent force fields in frog, Adaptive Motion of Animals and Machines (AMAM).
[Detail] [BibTeX] [PDF]

Peter Pastor, Heiko Hoffmann, and Stefan Schaal (2008). Movement generation by learning from demonstration and generalization to new targets, Adaptive Motion of Animals and Machines (AMAM).
[Detail] [BibTeX] [PDF]

Ting, J.-A.;D'Souza, A.;Vijayakumar, S.;Schaal, S. (2008). A Bayesian approach to empirical local linearizations for robotics, International Conference on Robotics and Automation (ICRA2008).
[Keywords: local linear models, bayesian approach, linearizations, machine learning,]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [PDF]

Park, D.-H.;Hoffmann, H.;Schaal, S. (2008). Combining dynamic movement primitives and potential fields for online obstacle avoidance, Adaptive Motion of Animals and Machines (AMAM).
[Keywords: movement primitives, potential fields, obstacle avoidance, dexterous manipulation]
[Detail] [BibTeX] [PDF]

Mistry, M.;Theodorou, E.;Liaw, G.;Yoshioka, T.;Schaal, S.;Kawato, M. (2008). An investigation of optimality in reaching movements with an acceleration based force field, Abstracts of the Society of Neuroscience Meeting (SFN 2008).
[Keywords: computational motor control, motor planning, optimization, force fields]
[Detail] [BibTeX]

Klanke, S.;Vijayakumar, S.;Schaal, S. (2008). A library for locally weighted projection regression, Journal of Machine Learning Research, 9, pp.623-626.
[Keywords: regression, local learning, online learning, c, c++, matlab, octave, python]
[Detail] [BibTeX] [PDF]

Hoffmann, H.;Schaal, S. (2008). Do humans plan continuous trajectories in kinematic coordinates?, Abstracts of the Society of Neuroscience Meeting (SFN 2008).
[Keywords: computational motor control, motor planning, representations, human subjects]
[Detail] [BibTeX]

Hoffmann, H.;Schaal, S. (2008). Human movement generation based on convergent flow fields: A computational model and a behavioral experiment, Advances in Computational Motor Control VII, Symposium at the Society for Neuroscience Meeting.
[Keywords: computational motor control, motor primitives, target switching]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [PDF]

Mistry, M., Theodorou, E., Hoffmann, H., Schaal, S. (2007). Uncertain 3D Force Fields in Reaching Movements: Do Humans Favor Robust or Average Performance?, Abstracts of the 37th Meeting of the Society of Neuroscience.
[Detail] [BibTeX] [PDF]

Mohajerian, P; Hoffmann, H.; Mistry, M.; Schaal, S. (2007). A Computational Model of Arm Trajectory Modification Using Dynamic Movement Primitives, Abstracts of the 37st Meeting of the Society of Neuroscience.
[Keywords: online movement correction, target switching, movement primitives, computational model, motor control]
[Detail] [BibTeX] [PDF]

Schaal, S; Mohajerian, P.; Ijspeert, A. (2007). Dynamics systems vs. optimal control — a unifying view, Progress in Brain Research, 165, pp.425-445.
[Keywords: discrete movement; rhythmic movement; movement primitives; dynamic systems; optimization; computational motor control]
[Detail] [BibTeX]

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]
[Detail] [BibTeX] [PDF]

Ting, J.; Theodorou, E.; Schaal, S. (2007). Learning an Outlier-Robust Kalman Filter, European Conference on Machine Learning (ECML 2007), pp.748-756, Springer.
[Keywords: automatic outlier detection, kalman filter, system dynamics, weighted least squares, bayesian statistical learning]
[Detail] [BibTeX] [PDF]

Ting, J.; D'Souza, A.; Yamamoto, K.; Yoshioka, T.; Hoffman, D.; Kakei, S.; Sergio, L.; Kalaska, J.; Kawato, M.; Strick, P.; Schaal, S. (2007). Using variational Bayesian least squares for EMG data prediction from M1 and premotor cortex neural firing, Abstracts of the 37th Meeting of the Society of Neuroscience.
[Keywords: motoneuron-muscle interface, emg prediction, m1, premotor cortex, feature selection, bayesian regression, computational neuroscience]
[Detail] [BibTeX] [PDF]

Ting, J.; Theodorou, E.; Schaal, S. (2007). Learning an Outlier-Robust Kalman Filter, CLMC Technical Report: TR-CLMC-2007-1.
[Keywords: automatic outlier detection, kalman filter, system dynamics, weighted least squares, bayesian statistical learning]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX]

Edakunni, N. U.;Schaal, S.;Vijayakumar, S. (2007). Kernel carpentry for onlne regression using randomly varying coefficient model, Proceedings of the 20th International Joint Conference on Artificial Intelligence.
[Keywords: bayesian weighted regression, variational bayes]
[Detail] [BibTeX] [PDF]

Mistry, M.;Nakanishi, J.;Schaal, S. (2007). Task space control with prioritization for balance and locomotion, IEEE International Conference on Intelligent Robotics Systems (IROS 2007).
[Keywords: operational space control, locomotion, balance, hierarchical]
[Detail] [BibTeX] [PDF]

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]
[Detail] [BibTeX] [PDF]

Nakanishi, J.;Mistry, M.;Schaal, S. (2007). Inverse dynamics control with floating base and constraints, International Conference on Robotics and Automation (ICRA2007), pp.1942-1947.
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX]

Pongas, D.;Mistry, M.;Schaal, S. (2007). A robust quadruped walking gait for traversing rough terrain, International Conference on Robotics and Automation (ICRA2007), pp.1474-1479.
[Keywords: quadruped locomotion, static walk, crawl gait, cog trajectory, rough terrain, internal-model control]
[Detail] [BibTeX] [PDF]

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]
[Detail] [BibTeX] [PDF]

Schaal, S. (2007). The new robotics - towards human-centered machines, HFSP Journal Frontiers of Interdisciplinary Research in the Life Sciences, 1, 2, pp.115-126.
[Keywords: assistive robotics, humanoid robotics, perspective]
[Detail] [BibTeX] [PDF]

Schaal, S. (2007). The computational neurobiology of reaching and pointing - a foundation for motor learning: By Reza Shadmehr and Steven P. Wise, Network, 18, 1, pp.1-3.
[Detail] [BibTeX] [PDF]

Ting, J.;Theodorou, E.;Schaal, S. (2007). A Kalman filter for robust outlier detection, IEEE International Conference on Intelligent Robotics Systems (IROS 2007).
[Keywords: kalman filter, variational bayes, outliers]
[Detail] [BibTeX] [PDF]

Ting, J.;D'Souza, A.;Schaal, S. (2007). Automatic outlier detection: A Bayesian approach, International Conference on Robotics and Automation (ICRA2007), pp.2489-2494.
[Keywords: weighted regression, outliers, bayesian statistics]
[Detail] [BibTeX] [PDF]

Ting, J.; Schaal, S. (2007). Bayesian Nonparametric Regression with Local Models, Workshop on Robotic Challenges for Machine Learning, NIPS 2007.
[Keywords: local models, bayesian nonparametric regression, machine learning, statistical learning]
[Detail] [BibTeX]

Hoffman, H.;Schaal, S. (2007). A computational model of human trajectory planning based on convergent flow fields, Abstracts of the 37st Meeting of the Society of Neuroscience.
[Keywords: motor control, computational neuroscience, behavior, motor primitives, force fields]
[Detail] [BibTeX]

Vijayakumar, S.;D'Souza, A.;Schaal, S. (2006). Approximate nearest neighbor regression in very high dimensions, in: Shakhnarovich, G.;Darrell, T.;Indyk, P. (eds.), Nearest-Neighbor Methods in Learning and Vision, pp.103-142, Cambridge, MA: MIT Press.
[Detail] [BibTeX]

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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [PDF]

Ting, J.;D'Souza, A.;Schaal, S. (2006). Bayesian regression with input noise for high dimensional data, Proceedings of the 23rd International Conference on Machine Leanring (ICML 2006).
[Keywords: bayesian regression linear models dimensionality reduction input noise rigid body dynamics parameter identification]
[Detail] [BibTeX] [PDF]

Ting, J.;Mistry, M.;Nakanishi, J.;Peters, J.;Schaal, S. (2006). A Bayesian approach to nonlinear parameter identification for rigid body dynamics, in: Burgard, W.;Sukhatme, G. S.;Schaal, S. (eds.), Robotics: Science and Systems (RSS 2006), Cambridge, MA: MIT Press.
[Keywords: bayesian regression linear models dimensionality reduction input noise rigid body dynamics parameter identification]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [PDF]

Nakanishi, J.;Farrell, J. A.;Schaal, S. (2005). Composite adaptive control with locally weighted statistical learning, Neural Networks, 18, 1, pp.71-90.
[Keywords: adaptive control, statistical learning, composite control law, provably stable, locally weighted regression]
[Detail] [BibTeX] [PDF]

Shibata, T.;Tabata, H.;Schaal, S.;Kawato, M. (2005). A model of smooth pursuit based on learning of the target dynamics using only retinal signals, Neural Networks, 18, pp.213-225.
[Keywords: oculomotor control learning biomimetic robotics internal models]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;D'Souza, A.;Schaal, S. (2005). Incremental online learning in high dimensions, Neural Computation, 17, 12, pp.2602-2634.
[Keywords: nonlinear regression locally weighted learning nonparametric partial least squares factor analysis confidence statistical learning dimensionality reduction principle components]
[Detail] [BibTeX] [PDF]

Mistry, M.;Mohajerian, P.;Schaal, S. (2005). Arm movement experiments with joint space force fields using an exoskeleton robot, IEEE Ninth International Conference on Rehabilitation Robotics, pp.408-413.
[Keywords: computational motor control trajectory planning inverse kinematics force control human motor control torque perturbations]
[Detail] [BibTeX] [PDF]

Schaal, S.;Schweighofer, N. (2005). Computational motor control in humans and robots, Curr Opin Neurobiol, 15, 6, pp.675-82.
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [PDF]

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), pp.1824-1831.
[Detail] [BibTeX] [PDF]

Ting, J.;D'Souza, A.;Yamamoto, K.;Yoshioka, T.;Hoffman, D.;Kakei, S.;Sergio, L.;Kalaska, J.;Kawato, M.;Strick, P.;Schaal, S. (2005). Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares, in: Weiss, Y.;Schölkopf, B.;Platt, J. (eds.), Advances in Neural Information Processing Systems 18 (NIPS 2005), Cambridge, MA: MIT Press.
[Keywords: bayesian regression, linear models, dimensionality reduction, feature selection, brain machine interfaces]
[Detail] [BibTeX] [PDF]

Pongas, D.;Billard, A.;Schaal, S. (2005). Rapbid synchronization and accurate phase-locking of rhythmic motor primitives, IEEE International Conference on Intelligent Robots and Systems (IROS 2005), pp.2911-2916.
[Keywords: earning from demonstration periodic movement phase locking rhythm generation rhythmic motor rhythmic movement pattern synchronization motor primitives periodic movement synchronization and phase locking learning from demonstration]
[Detail] [BibTeX] [PDF]

Billard, A.;Epars, Y.;Calinon, S.;Cheng, G.;Schaal, S. (2004). Discovering optimal imitation strategies, Robotics and Autonomous Systems, 47, 2-3, pp.68-77.
[Keywords: imitation, intent extraction, motor control]
[Detail] [BibTeX]

Nakanishi, J.;Farrell, J. A.;Schaal, S. (2004). Learning Composite Adaptive Control for a Class of Nonlinear Systems, IEEE International Conference on Robotics and Automation, pp.2647-2652.
[Keywords: adaptive control, learning, composite control law, provably stable, locally weighted regression]
[Detail] [BibTeX] [PDF]

Nakanishi, J.;Morimoto, J.;Endo, G.;Cheng, G.;Schaal, S.;Kawato, M. (2004). Learning from demonstration and adaptation of biped locomotion, Robotics and Autonomous Systems, 47, 2-3, pp.79-91.
[Keywords: movement primitives, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [PDF]

Nakanishi, J.;Morimoto, J.;Endo, G.;Cheng, G.;Schaal, S.;Kawato, M. (2004). A framework for learning biped locomotion with dynamic movement primitives, IEEE-RAS/RSJ International Conference on Humanoid Robots (Humanoids 2004), IEEE.
[Keywords: movement primitives, dynamic systems, locomotion, phase resetting, learning]
[Detail] [BibTeX] [PDF]

Nakanishi, J.;Schaal, S. (2004). Feedback error learning and nonlinear adaptive control, Neural Networks, 17, 10, pp.1453-1465.
[Keywords: adaptive control, feedback error learning, learning]
[Detail] [BibTeX] [PDF]

Schaal, S.;Ijspeert, A.;Billard, A. (2004). Computational approaches to motor learning by imitation, in: Frith, C. D.;Wolpert, D. (eds.), The Neuroscience of Social Interaction, 1431, pp.199-218, Oxford University Press.
[Keywords: imitation learning computational review movement primitives duality of movement generation and recognition motor control]
[Detail] [BibTeX] [PDF]

Schaal, S.;Peters, J.;Nakanishi, J.;Ijspeert, A. (2004). Learning Movement Primitives, International Symposium on Robotics Research (ISRR2003), Springer.
[Keywords: movement primitives, supervised learning, reinforcment learning, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [PDF]

Schaal, S.;Sternad, D.;Osu, R.;Kawato, M. (2004). Rhythmic movement is not discrete, Nature Neuroscience, 7, 10, pp.1137-1144.
[Keywords: fmri discrete rhythmic movement movement primitives]
[Detail] [BibTeX] [PDF]

Ting, J.; D'Souza, A.; Schaal, S. (2004). Predicting EMG Activity from Neural Firing in M1 with Bayesian Backfitting, Proceedings of the 11th Joint Symposium of Neural Computation (JSNC 2004).
[Keywords: bayesian backfitting, emg prediciton, m1, variational methods, linear models, statistical learning]
[Detail] [BibTeX] [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]
[Detail] [BibTeX]

Billard, A.;Epars, Y.;Schaal, S.;Cheng, G. (2003). Discovering imitation strategies through categorization of multi-cimensional data, IEEE International Conference on Intelligent Robots and Systems (IROS 2003).
[Keywords: movement primitives, sequencing]
[Detail] [BibTeX] [PDF]

D'Souza, A.;Vijayakumar, S.;Schaal, S. (2003). Bayesian backfitting, Proceedings of the 10th Joint Symposium on Neural Computation (JSNC 2003).
[Keywords: statistical learning, bayesian variational methods, linear regression, graphical models]
[Detail] [BibTeX] [PDF]

Ijspeert, A.;Nakanishi, J.;Schaal, S. (2003). Learning attractor landscapes for learning motor primitives, in: Becker, S.;Thrun, S.;Obermayer, K. (eds.), Advances in Neural Information Processing Systems 15, pp.1547-1554, Cambridge, MA: MIT Press.
[Keywords: learning nonlinear attractor landscapes movement primitives humanoid robotics statistical learning]
[Detail] [BibTeX] [PDF]

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]
[Detail] [BibTeX] [PDF]

Nakanishi, J.;Morimoto, J.;Endo, G.;Schaal, S.;Kawato, M. (2003). Learning from demonstration and adaptation of biped locomotion with dynamical movement primitives, Workshop on Robot Learning by Demonstration, IEEE International Conference on Intelligent Robots and Systems (IROS 2003).
[Keywords: movement primitives, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [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]
[Detail] [BibTeX] [PDF]

Schaal, S. (2003). Dynamic movement primitives - A framework for motor control in humans and humanoid robots, The International Symposium on Adaptive Motion of Animals and Machines.
[Keywords: movement primitives, behaviors, dynamic systems, computational motor control, attractor landscapes, fmri, behavioral evidence]
[Detail] [BibTeX] [PDF]

Schaal, S. (2003). Movement planning and imitation by shaping nonlinear attractors, Proceedings of the 12th Yale Workshop on Adaptive and Learning Systems.
[Keywords: movement primitives, behaviors, dynamic systems, computational motor control, attractor landscapes]
[Detail] [BibTeX] [PDF]

Schaal, S.;Ijspeert, A.;Billard, A. (2003). Computational approaches to motor learning by imitation, Philosophical Transaction of the Royal Society of London: Series B, Biological Sciences, 358, 1431, pp.537-547.
[Keywords: imitation learning, computational, review, movement primitives, duality of movement generation and recognition, motor control]
[Detail] [BibTeX] [PDF]

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).
[Keywords: movement primitives, supervised learning, reinforcment learning, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [PDF]

Ijspeert, J. A.;Nakanishi, J.;Schaal, S. (2002). Movement imitation with nonlinear dynamical systems in humanoid robots, International Conference on Robotics and Automation (ICRA2002).
[Keywords: movement primitives, behaviors, dynamic systems, computational motor control, attractor landscapes, humanoid robotics, overall best paper award]
[Detail] [BibTeX] [PDF]

Ijspeert, J. A.;Nakanishi, J.;Schaal, S. (2002). Learning rhythmic movements by demonstration using nonlinear oscillators, IEEE International Conference on Intelligent Robots and Systems (IROS 2002), pp.958-963, Piscataway, NJ: IEEE.
[Keywords: movement primitives, behaviors, dynamic systems, computational motor control, attractor landscapes, discrete, rhythmic]
[Detail] [BibTeX] [PDF]

Mehta, B.;Schaal, S. (2002). Forward models in visuomotor control, J Neurophysiol, 88, 2, pp.942-53.
[Keywords: internal models, forward models, delay compensation, blank out, pole balancing, predictive control]
[Detail] [BibTeX] [PDF]

Nakanishi, J.;Farrell, J. A.;Schaal, S. (2002). A locally weighted learning composite adaptive controller with structure adaptation, IEEE International Conference on Intelligent Robots and Systems (IROS 2002).
[Keywords: adaptive control, learning, composite control law, provably stable, locally weighted regression]
[Detail] [BibTeX] [PDF]

Schaal, S. (2002). Learning robot control, in: Arbib, M. A. (eds.), The handbook of brain theory and neural networks, 2nd Edition, pp.983-987, MIT Press.
[Keywords: robot learning, review, reinforcement learning, supervised learning, real-time learning]
[Detail] [BibTeX] [PDF]

Schaal, S. (2002). Arm and hand movement control, in: Arbib, M. A. (eds.), The handbook of brain theory and neural networks, 2nd Edition, pp.110-113, MIT Press.
[Detail] [BibTeX] [PDF]

Schaal, S.;Atkeson, C. G.;Vijayakumar, S. (2002). Scalable techniques from nonparameteric statistics for real-time robot learning, Applied Intelligence, 17, 1, pp.49-60.
[Keywords: statistical learning, nonparametric regression, distance metric, dimensionality reduction, high dimensional learning, robot learning, real-time learning]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;D'Souza, A.;Shibata, T.;Conradt, J.;Schaal, S. (2002). Statistical learning for humanoid robots, Autonomous Robots, 12, 1, pp.59-72.
[Keywords: statistical learning, nonparametric regression, distance metric, dimensionality reduction, high dimensional learning, humanoid robotics, oculomotor control, internal models]
[Detail] [BibTeX] [PDF]

Billard, A.;Schaal, S. (2001). Robust learning of arm trajectories through human demonstration, IEEE International Conference on Intelligent Robots and Systems (IROS 2001), Piscataway, NJ: IEEE.
[Keywords: imitation learning, movement primitives, humanoid robotics]
[Detail] [BibTeX] [PDF]

D'Souza, A.;Vijayakumar, S.;Schaal, S. (2001). Learning inverse kinematics, IEEE International Conference on Intelligent Robots and Systems (IROS 2001), Piscataway, NJ: IEEE.
[Keywords: inverse kinematics, humanoid robotics, high dimensional, resolved motion rate control, local learning, null space optimization]
[Detail] [BibTeX] [PDF]

Ijspeert, A.;Nakanishi, J.;Schaal, S. (2001). Trajectory formation for imitation with nonlinear dynamical systems, IEEE International Conference on Intelligent Robots and Systems (IROS 2001), pp.752-757.
[Keywords: movement primitives behaviors dynamic systems computational motor control attractor landscapes]
[Detail] [BibTeX] [PDF]

Ijspeert, A. J.;Nakanishi, J.;Shibata, T.;Schaal, S. (2001). Nonlinear dynamical systems for imitation with humanoid robots, Humanoids2001, Second IEEE-RAS International Conference on Humanoid Robots.
[Keywords: movement primitives, behaviors, dynamic systems, computational motor control, attractor landscapes, humanoid robotics]
[Detail] [BibTeX] [PDF]

Kotosaka, S.;Schaal, S. (2001). Synchronized robot drumming by neural oscillator, Journal of the Robotics Society of Japan, 19, 1, pp.116-123.
[Keywords: movement primitives, behaviors, dynamic systems, computational motor control, attractor landscapes, humanoid robotics, drumming, synchronization, best annual paper award of the japanese robotics society]
[Detail] [BibTeX]

Schaal, S.;Sternad, D. (2001). Origins and violations of the 2/3 power law in rhythmic 3D movements, Experimental Brain Research, 136, pp.60-72.
[Keywords: computational motor control, trajectory planning, power law, movement segmentation, motor primitives, rhythmic movement]
[Detail] [BibTeX] [PDF]

Schaal, S.;Vijayakumar, S.;D'Souza, A.;Ijspeert, A.;Nakanishi, J. (2001). Real-time statistical learning for robotics and human augmentation, in: Jarvis, R. A.;Zelinsky, A. (eds.), International Symposium on Robotics Research.
[Keywords: humanoid robotics, statistical learning, movement primitives, real-time learning]
[Detail] [BibTeX] [PDF]

Shams, L.;Schaal, S. (2001). Graph-matching vs. entropy-based methods for object detection, Neural Networks, 14, 3, pp.345-354.
[Keywords: object recognition, computer vision, statistical learning, nonparametric density estimation, graph matching, entropy, mutual information]
[Detail] [BibTeX] [PDF]

Shibata, T.;Schaal, S. (2001). Biomimetic gaze stabilization based on feedback-error learning with nonparametric regression networks, Neural Networks, 14, 2, pp.201-216.
[Keywords: oculomotor control, cerebellum, vor, okr, learning, locally weighted learning, feedback error learning, best annual paper award of the japanese neural networks society]
[Detail] [BibTeX] [PDF]

Shibata, T.;Schaal, S. (2001). Fast learning of biomimetic oculomotor control with nonparametric regression networks (in Japanese), Journal of the Robotics Society of Japan, 19, 4, pp.468-479.
[Detail] [BibTeX]

Shibata, T.;Schaal, S. (2001). Biomimetic smooth pursuit based on fast learning of the target dynamics, IEEE International Conference on Intelligent Robots and Systems (IROS 2001).
[Keywords: oculomotor control, cerebellum, smooth pursuit learning, locally weighted learning, tracking, target dynamics]
[Detail] [BibTeX] [PDF]

Shibata, T.;Vijayakumar, S.;Conradt, J.;Schaal, S. (2001). Biomimetic oculomotor control, Adaptive Behavior, 9, 3/4, pp.189-207.
[Keywords: oculomotor control, cerebellum, smooth pursuit learning, locally weighted learning, tracking, target dynamics, visual attention, humanoid robotics]
[Detail] [BibTeX] [PDF]

Shibata, T.;Vijayakumar, S.;Conradt, J.;Schaal, S. (2001). Humanoid oculomotor control based on concepts of computational neuroscience, Humanoids2001, Second IEEE-RAS International Conference on Humanoid Robots.
[Keywords: oculomotor control, smooth pursuit learning, locally weighted learning, tracking, target dynamics, vor, visual attention, okr]
[Detail] [BibTeX] [PDF]

Sternad, D.;Duarte, M.;Katsumata, H.;Schaal, S. (2001). Bouncing a ball: Tuning into dynamic stability, Journal of Experimental Psychology: Human Perception and Performance, 27, 5, pp.1163-1184.
[Keywords: dynamic systems approach, computational motor control, task dynamics, perception-action coupling, movement primitives]
[Detail] [BibTeX]

Vijayakumar, S.;Conradt, J.;Shibata, T.;Schaal, S. (2001). Overt visual attention for a humanoid robot, IEEE International Conference on Intelligent Robots and Systems (IROS 2001).
[Keywords: oculomotor control, visual attention, dynamic fields, saccades]
[Detail] [BibTeX] [PDF]

Atkeson, C. G.;Hale, J.;Kawato, M.;Kotosaka, S.;Pollick, F.;Riley, M.;Schaal, S.;Shibata, S.;Tevatia, G.;Ude, A. (2000). Using Humanoid Robots to Study Human Behaviour, IEEE Intelligent Systems, 15, 4, pp.46-56.
[Keywords: humanoid robotics, motor primitives, motion capture, computational motor control]
[Detail] [BibTeX] [PDF]

Conradt, J.;Tevatia, G.;Vijayakumar, S.;Schaal, S. (2000). On-line learning for humanoid robot systems, Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), 1, pp.191-198.
[Keywords: humanoid robotics, on-line learning, nonparametric regression, supersmoothing, incremental]
[Detail] [BibTeX] [PDF]

Kotosaka, S.;Schaal, S. (2000). Synchronized robot drumming by neural oscillator, The International Symposium on Adaptive Motion of Animals and Machines.
[Keywords: trajectory formation, learning, nonlinear dynamics, motor skill acquisition, pattern generators, drumming]
[Detail] [BibTeX] [PDF]

Kotosaka, S.;Shibata, T.;Schaal, S. (2000). Humanoid Robot DB, Proceedings of the International Conference on Machine Automation (ICMA2000), pp.21-26.
[Keywords: humanoid robotics, computational motor control]
[Detail] [BibTeX]

Schaal, S.;Atkeson, C. G.;Vijayakumar, S. (2000). Real-time robot learning with locally weighted statistical learning, International Conference on Robotics and Automation (ICRA2000).
[Keywords: real-time robot learning, statistical learning, humanoid robotics, finalist for overall best paper award]
[Detail] [BibTeX] [PDF]

Schaal, S.;Kotosaka, S.;Sternad, D. (2000). Nonlinear dynamical systems as movement primitives, Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings.
[Keywords: trajectory formation, learning, nonlinear dynamics, motor skill acquisition, pattern generators]
[Detail] [BibTeX] [PDF]

Schaal, S.;Sternad, D.;Dean, W.;Kotoska, S.;Osu, R.;Kawato, M. (2000). Reciprocal excitation between biological and robotic research, Sensor Fusion and Decentralized Control in Robotic Systems III, Proceedings of SPIE, 4196, pp.30-40.
[Keywords: humanoid robotics, computational motor control, neuroscience, dynamic systems approach, pattern generators]
[Detail] [BibTeX] [PDF]

Shibata, T.;Schaal, S. (2000). Biomimetic gaze stabilization, in: Demiris, J.;Birk, A. (eds.), Robot learning: an Interdisciplinary approach, pp.31-52, World Scientific.
[Keywords: oculomotor control, cerebellum, vor, okr, learning, locally weighted learning, feedback error learning]
[Detail] [BibTeX] [PDF]

Shibata, T.;Schaal, S. (2000). Fast learning of biomimetic oculomotor control with nonparametric regression networks, International Conference on Robotics and Automation (ICRA2000), pp.3847-3854.
[Keywords: oculomotor control, cerebellum, vor, okr, learning, locally weighted learning, feedback error learning]
[Detail] [BibTeX] [PDF]

Sternad, D.;Dean, W. J.;Schaal, S. (2000). Interaction of rhythmic and discrete pattern generators in single joint movements, Human Movement Science, 19, 4, pp.627-665.
[Keywords: movement primitives, behaviors, dynamic systems, computational motor control, movement sequencing, discrete, rhythmic, superposition, phase resetting]
[Detail] [BibTeX] [PDF]

Sternad, D.;Duarte, M.;Katsumata, H.;Schaal, S. (2000). Dynamics of a bouncing ball in human performance, Physical Review E, 63, 011902, pp.1-8.
[Keywords: dynamic systems approach, computational motor control, task dynamics, perception-action coupling, movement primitives, special press comment]
[Detail] [BibTeX] [PDF]

Tevatia, G.;Schaal, S. (2000). Inverse kinematics for humanoid robots, International Conference on Robotics and Automation (ICRA2000), pp.294-299.
[Keywords: inverse kinematics humanoid robotics high dimensional resolved motion rate control efficient extended jacobian]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;Schaal, S. (2000). Locally weighted projection regression: An O(n) algorithm for incremental real time learning in high dimensional spaces, Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), 1, pp.288-293.
[Keywords: nonparametric regression, linear models, principle components, dimensionality reduction, supersmoothing, highdimensional regression]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;Schaal, S. (2000). Fast and efficient incremental learning for high-dimensional movement systems, International Conference on Robotics and Automation (ICRA2000).
[Keywords: robot learning, humanoids, high-dimensional, locally weighted regression, dimensionality reduction, partial least squares]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;Schaal, S. (2000). Real Time Learning in Humanoids: A challenge for scalability of Online Algorithms, Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings.
[Keywords: humanoid robotics, learning, high-dimensional, internal models, locally weighted regression]
[Detail] [BibTeX] [PDF]

Schaal, S. (1999). Is imitation learning the route to humanoid robots?, Trends in Cognitive Sciences, 3, 6, pp.233-242.
[Keywords: imitation learning, movement primitives, humanoid robotics, review, internal models]
[Detail] [BibTeX] [PDF]

Schaal, S. (1999). Nonparametric regression for learning nonlinear transformations, in: Ritter, H.;Cruse, H.;Dean, J. (eds.), Prerational Intelligence in Strategies, High-Level Processes and Collective Behavior, 2, pp.595-621, Kluwer Academic Publishers.
[Keywords: nonparametric regression, learning, review, statistical learning, lazy learning]
[Detail] [BibTeX] [PDF]

Sternad, D.;Schaal, D. (1999). Segmentation of endpoint trajectories does not imply segmented control, Experimental Brain Research, 124, 1, pp.118-136.
[Keywords: trajectory formation, segementation, movement primitives, motor control, piecewise planarity]
[Detail] [BibTeX] [PDF]

Schaal, S.;Atkeson, C. G. (1998). Constructive incremental learning from only local information, Neural Computation, 10, 8, pp.2047-2084.
[Keywords: statistical learning, nonparametric regression, distance metric, incremental learning, on-line learning, supersmoothing]
[Detail] [BibTeX] [PDF]

Schaal, S.;Sternad, D. (1998). Programmable pattern generators, 3rd International Conference on Computational Intelligence in Neuroscience, pp.48-51.
[Keywords: movement primitives behaviors dynamic systems computational motor control attractor landscapes]
[Detail] [BibTeX] [PDF]

Schaal, S.;Vijayakumar, S.;Atkeson, C. G. (1998). Local dimensionality reduction, in: Jordan, M. I.;Kearns, M. J.;Solla, S. A. (eds.), Advances in Neural Information Processing Systems 10, pp.633-639, MIT Press.
[Keywords: dimensionality reduction, partial least squares, pca, regression, high dimensions, local]
[Detail] [BibTeX] [PDF]

Shibata, T.;Schaal, S. (1998). Biomimetic gaze stabilization based on a study of the vestibulocerebellum, European Workshop on Learning Robots, pp.84-94.
[Keywords: oculomotor control, cerebellum, vor, okr, learning, locally weighted learning, feedback error learning]
[Detail] [BibTeX] [PDF]

Shibata, T.;Schaal, S. (1998). Towards biomimetic vision, International Conference on Intelligence Robots and Systems, pp.872-879.
[Keywords: oculomotor control, cerebellum, vor, okr, learning, locally weighted learning, feedback error learning]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;Schaal, S. (1998). Local adaptive subspace regression, Neural Processing Letters, 7, 3, pp.139-149.
[Keywords: nonparametric regression, linear models, principle components, dimensionality reduction, supersmoothing]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;Schaal, S. (1998). Robust local learning in high dimensional spaces, 5th Joint Symposium on Neural Computation, pp.186-193, Institute for Neural Computation, University of California, San Diego.
[Keywords: nonparametric regression, linear models, principle components, dimensionality reduction, supersmoothing]
[Detail] [BibTeX]

Atkeson, C. G.;Moore, A. W.;Schaal, S. (1997). Locally weighted learning, Artificial Intelligence Review, 11, 1-5, pp.11-73.
[Keywords: statistical learning, nonparametric regression, distance metric, lazy learning]
[Detail] [BibTeX] [PDF]

Atkeson, C. G.;Moore, A. W.;Schaal, S. (1997). Locally weighted learning for control, Artificial Intelligence Review, 11, 1-5, pp.75-113.
[Keywords: statistical learning, nonparametric regression, distance metric, lazy learning, learning control, reinforcement learning]
[Detail] [BibTeX] [PDF]

Atkeson, C. G.;Schaal, S. (1997). Robot learning from demonstration, in: Fisher Jr., D. H. (eds.), Machine Learning: Proceedings of the Fourteenth International Conference (ICML '97), pp.12-20, Morgan Kaufmann.
[Keywords: imitation learning, reinforcement learning, dynamic programming, motor skills]
[Detail] [BibTeX] [PDF]

Atkeson, C. G.;Schaal, S. (1997). Learning tasks from a single demonstration, IEEE International Conference on Robotics and Automation (ICRA97), 2, pp.1706-1712, Piscataway, NJ: IEEE.
[Keywords: learning from demonstration, imitation, reinforcement learning]
[Detail] [BibTeX] [PDF]

Schaal, S. (1997). Learning from demonstration, in: Mozer, M. C.;Jordan, M.;Petsche, T. (eds.), Advances in Neural Information Processing Systems 9, pp.1040-1046, MIT Press.
[Keywords: imitation learning, movement primitives, reinforcement learning, shaping, priming]
[Detail] [BibTeX] [PDF]

Vijayakumar, S.;Schaal, S. (1997). Local dimensionality reduction for locally weighted learning, International Conference on Computational Intelligence in Robotics and Automation, pp.220-225.
[Keywords: statistical learning, nonparametric regression, distance metric, dimensionality reduction, high dimensional learning]
[Detail] [BibTeX] [PDF]

Miyamoto, H.;Gandolfo, F.;Gomi, H.;Schaal, S.;Koike, Y.;Rieka, O.;Nakano, E.;Wada, Y.;Kawato, M. (1996). A kendama learning robot based on a dynamic optimiation principle, Preceedings of the International Conference on Neural Information Processing, pp.938-942.
[Keywords: teaching by showing, task-level learning, dynamic optimization, imitation, humanoid robots]
[Detail] [BibTeX]

Miyamoto, H.;Schaal, S.;Gandolfo, F.;Koike, Y.;Osu, R.;Nakano, E.;Wada, Y.;Kawato, M. (1996). A Kendama learning robot based on bi-directional theory, Neural Networks, 9, 8, pp.1281-1302.
[Keywords: teaching by showing, task-level learning, dynamic optimization, imitation, humanoid robots]
[Detail] [BibTeX] [PDF]

Schaal, S.;Atkeson, C. G. (1996). From isolation to cooperation: An alternative of a system of experts, in: Touretzky, D. S.;Mozer, M. C.;Hasselmo, M. E. (eds.), Advances in Neural Information Processing Systems 8, pp.605-611, MIT Press.
[Keywords: statistical learning, nonparametric regression, distance metric, supersmoothing, mixture model, incremental learning]
[Detail] [BibTeX] [PDF]

Schaal, S.;Sternad, D.;Atkeson, C. G. (1996). One-handed juggling: A dynamical approach to a rhythmic movement task, Journal of Motor Behavior, 28, 2, pp.165-183.
[Keywords: biological motor control, trajectory formation, nonlinear dynamics, task dynamics, movement primitives]
[Detail] [BibTeX] [PDF]

Atkeson, C. G.;Schaal, S. (1995). Memory-based neural networks for robot learning, Neurocomputing, 9, pp.1-27.
[Keywords: memory-based learning, juggling, locally weighted regression, nearest neighbor, internal models]
[Detail] [BibTeX] [PDF]

Miyamoto, H.;Gandolfo, F.;Gomi, H.;Schaal, S.;Koike, Y.;Osu, R.;Nakano, E.;Kawato, M. (1995). A kendama learning robot based on a dynamic optimization theory, Preceedings of the 4th IEEE International Workshop on Robot and Human Communication (RO-MAN'95), pp.327-332.
[Keywords: learning from demonstration, internal models, via points, robot learning, imitation, biomimetic robotics, reinforcement learning]
[Detail] [BibTeX]

Schaal, S.;Atkeson, C. G. (1995). Robot learning by nonparametric regression, in: Graefe, V. (eds.), Intelligent Robots and Systems, pp.137-153, Elsevier.
[Keywords: nonparametric regression, memory-based learning, statistical, robot, juggling]
[Detail] [BibTeX] [PDF]

Sternad, D.;Schaal, S.;Atkeson, C. G. (1995). Batting a ball: Dynamics of a rhythmic skill, in: Bardy, B.;Bostma, R.;Guiard, Y. (eds.), Studies in Perception and Action, pp.119-122, Erlbaum.
[Keywords: motor control, nonlinear dynamics, task dynamics, ball bouncing, open-loop stability]
[Detail] [BibTeX]

Schaal, S. (1994). Nonparametric regression for learning, Conference on Adaptive Behavior and Learning, Center of Interdisciplinary Research (ZIF) Bielefeld Germany, also technical report TR-H-098 of the ATR Human Information Processing Research Laboratories.
[Keywords: nonparametric regression, review, statistical learning]
[Detail] [BibTeX] [PDF]

Schaal, S.;Atkeson, C. G. (1994). Robot juggling: An implementation of memory-based learning, Control Systems Magazine, 14, 1, pp.57-71.
[Keywords: nonparametric regression, memory-based learning, statistical, robot, juggling]
[Detail] [BibTeX] [PDF]

Schaal, S.;Atkeson, C. G. (1994). Assessing the quality of learned local models, in: Cowan, J.;Tesauro, G.;Alspector, J. (eds.), Advances in Neural Information Processing Systems 6, pp.160-167, Morgan Kaufmann.
[Keywords: nonparametric regression, confidence measures, exploration, linear models]
[Detail] [BibTeX] [PDF]

Schaal, S.;Atkeson, C. G. (1994). Robot learning by nonparametric regression, Proceedings of the International Conference on Intelligent Robots and Systems (IROS'94), pp.478-485, Munich Germany.
[Keywords: nonparametric regression, memory-based learning, statistical, robot, juggling]
[Detail] [BibTeX]

Schaal, S.;Atkeson, C. G. (1994). Memory-based robot learning, IEEE International Conference on Robotics and Automation, 3, pp.2928-2933.
[Keywords: nonparametric regression, memory-based learning, statistical, robot, juggling]
[Detail] [BibTeX]

Atkeson, C. G.;Schaal, S. (1993). Roles for memory-based learning in robotics, Proceedings of the Sixth International Symposium on Robotics Research, pp.503-521.
[Keywords: statistical learning, robotics, nonparametric regression]
[Detail] [BibTeX]

Schaal, S.;Atkeson, C. G. (1993). Open loop stable control strategies for robot juggling, IEEE International Conference on Robotics and Automation, 3, pp.913-918, Piscataway, NJ: IEEE.
[Keywords: trajectory formation nonlinear nynamics motor skill acquisition]
[Detail] [BibTeX] [PDF]

Schaal, S.;Ehrlenspiel, K. (1993). Design concurrent calculation: A CAD- and data-integrated approach, Journal of Engineering Design, 4, pp.71-85.
[Keywords: computer-aided desing, knowledge-based reasoning, sql-databases, artificial intelligence]
[Detail] [BibTeX]

Schaal, S.;Sternad, D. (1993). Learning passive motor control strategies with genetic algorithms, in: Nadel, L.;Stein, D. (eds.), 1992 Lectures in complex systems, pp.913-918, Addison-Wesley.
[Keywords: trajectory formation, learning, nonlinear nynamics, motor skill acquisition]
[Detail] [BibTeX] [PDF]

Sternad, D.;Schaal, S. (1993). A genetic algorithm for evolution from an ecological perspective, in: Nadel, L.;Stein, D. (eds.), 1992 Lectures in Complex Systems, pp.223-231, Addison-Wesley.
[Keywords: artificial life, complex systems]
[Detail] [BibTeX]

Ehrlenspiel, K.;Schaal, S. (1992). Ins CAD integrierte Kostenkalkulation (CAD-Integrated Cost Calculation), Konstruktion 44, 12, pp.407-414.
[Keywords: computer aided design, sql, knowledge-based systems, design-concurrent calculation]
[Detail] [BibTeX]

Schaal, S. (1992). Integrierte Wissensverarbeitung mit CAD am Beispiel der konstruktionsbegleitenden Kalkulation (Ways to smarter CAD Systems), Hanser 1992. (Konstruktionstechnik München Band 8). Zugl. München: TU Diss..
[Keywords: computer-aided desing, knowledge-based reasoning, sql-databases, artificial intelligence]
[Detail] [BibTeX]

Schaal, S. (1992). Informationssysteme mit CAD (Information systems within CAD), in: Milberg, J. (eds.), CAD/CAM Grundlagen, pp.199-204, Springer.
[Keywords: computer-aided desing, knowledge-based reasoning, sql-databases, artificial intelligence]
[Detail] [BibTeX]

Schaal, S.;Atkeson, C. G.;Botros, S. (1992). What should be learned?, Proceedings of Seventh Yale Workshop on Adaptive and Learning Systems, pp.199-204.
[Keywords: trajectory formation nonlinear nynamics motor skill acquisition]
[Detail] [BibTeX]

Ehrlenspiel, K.;Schaal, S. (1991). Ways to smarter CAD-systems, in: Hubka (eds.), Proceedings of ICED'91Heurista, pp.10-16, Edition.
[Keywords: computer aided design, sql, knowledge-based systems, design-concurrent calculation]
[Detail] [BibTeX]