On Model-free Reinforcement Learning for Switched Linear Systems: A Subspace Clustering Approach
暂无分享,去创建一个
[1] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[2] Gilad Lerman,et al. Median K-Flats for hybrid linear modeling with many outliers , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.
[3] Alessandro Abate,et al. Efficient suboptimal solutions of switched LQR problems , 2009, 2009 American Control Conference.
[4] R. Vidal,et al. Sparse Subspace Clustering: Algorithm, Theory, and Applications. , 2013, IEEE transactions on pattern analysis and machine intelligence.
[5] Jieping Ye,et al. An accelerated gradient method for trace norm minimization , 2009, ICML '09.
[6] F. Lewis,et al. Reinforcement Learning and Feedback Control: Using Natural Decision Methods to Design Optimal Adaptive Controllers , 2012, IEEE Control Systems.
[7] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[8] Sergey Levine,et al. Continuous Deep Q-Learning with Model-based Acceleration , 2016, ICML.
[9] P. Tseng. Nearest q-Flat to m Points , 2000 .
[10] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[11] David Silver,et al. Deep Reinforcement Learning with Double Q-Learning , 2015, AAAI.
[12] P J Webros. BACKPROPAGATION THROUGH TIME: WHAT IT DOES AND HOW TO DO IT , 1990 .
[13] Christopher M. Bishop,et al. Mixtures of Probabilistic Principal Component Analyzers , 1999, Neural Computation.
[14] Frank L. Lewis,et al. Online actor critic algorithm to solve the continuous-time infinite horizon optimal control problem , 2009, 2009 International Joint Conference on Neural Networks.
[15] S. Shankar Sastry,et al. Generalized Principal Component Analysis , 2016, Interdisciplinary applied mathematics.
[16] Alex Graves,et al. Playing Atari with Deep Reinforcement Learning , 2013, ArXiv.
[17] René Vidal,et al. Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Daniel Liberzon,et al. Switching in Systems and Control , 2003, Systems & Control: Foundations & Applications.
[19] Alec Radford,et al. Proximal Policy Optimization Algorithms , 2017, ArXiv.
[20] Frank L. Lewis,et al. Adaptive optimal control for continuous-time linear systems based on policy iteration , 2009, Autom..
[21] Luigi Fortuna,et al. Reinforcement Learning and Adaptive Dynamic Programming for Feedback Control , 2009 .
[22] René Vidal,et al. Sparse subspace clustering , 2009, CVPR.
[23] Anil A. Bharath,et al. Deep Reinforcement Learning: A Brief Survey , 2017, IEEE Signal Processing Magazine.
[24] Jianghai Hu,et al. Infinite-Horizon Switched LQR Problems in Discrete Time: A Suboptimal Algorithm With Performance Analysis , 2012, IEEE Transactions on Automatic Control.
[25] Frank L. Lewis,et al. Reinforcement Q-learning for optimal tracking control of linear discrete-time systems with unknown dynamics , 2014, Autom..
[26] John N. Tsitsiklis,et al. Neuro-dynamic programming: an overview , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.
[27] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[28] René Vidal,et al. Low rank subspace clustering (LRSC) , 2014, Pattern Recognit. Lett..
[29] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[30] Nikolai Matni,et al. On the Sample Complexity of the Linear Quadratic Regulator , 2017, Foundations of Computational Mathematics.
[31] Dimitri P. Bertsekas,et al. Dynamic Programming and Optimal Control, Two Volume Set , 1995 .
[32] Sergey Levine,et al. Trust Region Policy Optimization , 2015, ICML.
[33] Frank L. Lewis,et al. Linear Quadratic Tracking Control of Partially-Unknown Continuous-Time Systems Using Reinforcement Learning , 2014, IEEE Transactions on Automatic Control.
[34] Derong Liu,et al. Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems , 2015, IEEE Transactions on Neural Networks and Learning Systems.