Learned graphical models for probabilistic planning provide a new class of movement primitives
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Marc Toussaint | Wolfgang Maass | Gerhard Neumann | Elmar A. Rückert | G. Neumann | Marc Toussaint | W. Maass | E. Rückert
[1] Jan Peters,et al. Learning complex motions by sequencing simpler motion templates , 2009, ICML '09.
[2] Duy Nguyen-Tuong,et al. Local Gaussian Process Regression for Real Time Online Model Learning , 2008, NIPS.
[3] A. Billard,et al. Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models , 2011, IEEE Transactions on Robotics.
[4] Stefan Schaal,et al. 2008 Special Issue: Reinforcement learning of motor skills with policy gradients , 2008 .
[5] E. Todorov,et al. A generalized iterative LQG method for locally-optimal feedback control of constrained nonlinear stochastic systems , 2005, Proceedings of the 2005, American Control Conference, 2005..
[6] Gerhard Neumann,et al. Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation , 2013, Artificial Life.
[7] Stefan Schaal,et al. Learning and generalization of motor skills by learning from demonstration , 2009, 2009 IEEE International Conference on Robotics and Automation.
[8] Steven M. LaValle,et al. RRT-connect: An efficient approach to single-query path planning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).
[9] Petros Koumoutsakos,et al. Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) , 2003, Evolutionary Computation.
[10] Verena Heidrich-Meisner,et al. Neuroevolution strategies for episodic reinforcement learning , 2009, J. Algorithms.
[11] Christian Igel,et al. Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search , 2009, ICML '09.
[12] Bernhard Schölkopf,et al. Learning Inverse Dynamics: a Comparison , 2008, ESANN.
[13] Marc Toussaint,et al. Robot trajectory optimization using approximate inference , 2009, ICML '09.
[14] Robert A. Jacobs,et al. Properties of Synergies Arising from a Theory of Optimal Motor Behavior , 2006, Neural Computation.
[15] Jun Nakanishi,et al. Learning Attractor Landscapes for Learning Motor Primitives , 2002, NIPS.
[16] Vicenç Gómez,et al. Optimal control as a graphical model inference problem , 2009, Machine Learning.
[17] H. Kappen. An introduction to stochastic control theory, path integrals and reinforcement learning , 2007 .
[18] Michael I. Jordan,et al. Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.
[19] Stefan Schaal,et al. Incremental Online Learning in High Dimensions , 2005, Neural Computation.
[20] Aude Billard,et al. Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models , 2011, IEEE Transactions on Robotics.
[21] Emilio Bizzi,et al. Combinations of muscle synergies in the construction of a natural motor behavior , 2003, Nature Neuroscience.
[22] E. Bizzi,et al. Article history: , 2005 .
[23] Jan Peters,et al. Noname manuscript No. (will be inserted by the editor) Policy Search for Motor Primitives in Robotics , 2022 .
[24] Tom Schaul,et al. Episodic Reinforcement Learning by Logistic Reward-Weighted Regression , 2008, ICANN.
[25] Andrew W. Moore,et al. Locally Weighted Learning for Control , 1997, Artificial Intelligence Review.
[26] Christopher G. Atkeson,et al. Multiple balance strategies from one optimization criterion , 2007, 2007 7th IEEE-RAS International Conference on Humanoid Robots.
[27] Jun Nakanishi,et al. Learning Movement Primitives , 2005, ISRR.
[28] Frank Sehnke,et al. Parameter-exploring policy gradients , 2010, Neural Networks.
[29] M. Carpenter. The Co-ordination and Regulation of Movements , 1968 .
[30] Andrea d'Avella,et al. Modularity for Sensorimotor Control: Evidence and a New Prediction , 2010, Journal of motor behavior.
[31] Jan Peters,et al. Reinforcement Learning to Adjust Robot Movements to New Situations , 2010, IJCAI.
[32] Ronald J. Williams,et al. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , 2004, Machine Learning.
[33] Stefan Schaal,et al. Reinforcement learning of motor skills in high dimensions: A path integral approach , 2010, 2010 IEEE International Conference on Robotics and Automation.
[34] Jun Nakanishi,et al. A Unifying Methodology for Robot Control with Redundant DOFs , 2008 .
[35] Sethu Vijayakumar,et al. Adaptive Optimal Feedback Control with Learned Internal Dynamics Models , 2010, From Motor Learning to Interaction Learning in Robots.