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We develop the first end-to-end sample complexity of model-free policy gradient (PG) methods in discrete-time infinite-horizon Kalman filtering.
A new approach to linear filtering and prediction problems
Rudolf E Kalman · 1960
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On the general theory of control systems
Rudolf E Kalman · 1960
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Introduction to Stochastic Control Theory
Karl J Astrom · 1971
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Guaranteed margins for lqg regulators
John C Doyle · 1978
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Optimal Filtering
Brian DO Anderson and John B Moore · 1979
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Convergence properties of the Riccati difference equation in optimal filtering of nonstabilizable systems
Siew Chan, GC Goodwin, and Kwai Sin · 1984
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Monotonicity and stabilizability-properties of solutions of the riccati difference equation: Propositions, lemmas, theorems, fallacious conjectures and counterexamples
Robert R Bitmead, Michel R Gevers, Ian R Petersen, and R John Kaye · 1985
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Monotonicity and stabilizability results for the solutions of the riccati difference equation
CE De Souza · 1989
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Optimal Control: Linear Quadratic Methods
Brian DO Anderson and John B Moore · 1990
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Indefinite-Quadratic Estimation and Control: A Unified Approach to H 2 H_{2} and H ∞ H_{\infty} Theories
Babak Hassibi, Ali H Sayed, and Thomas Kailath · 1999
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Policy gradient methods for reinforcement learning with function approximation
Richard S Sutton, David A McAllester, Satinder P Singh, and Yishay Mansour · 2000
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Control Theory: Twenty-five Seminal Papers (1931-1981)
Tamer Başar · 2001
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A natural policy gradient
Sham M Kakade · 2002
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Least-squares policy iteration
Michail G Lagoudakis and Ronald Parr · 2003
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Making gradient descent optimal for strongly convex stochastic optimization
Alexander Rakhlin, Ohad Shamir, and Karthik Sridharan · 2011
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Optimal rates for zero-order convex optimization: The power of two function evaluations
John C Duchi, Michael I Jordan, Martin J Wainwright, and Andre Wibisono · 2015
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Continuous control with deep reinforcement learning
Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2015
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A tour of reinforcement learning: The view from continuous control
Benjamin Recht · 2019
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Learning the globally optimal distributed LQ regulator
Luca Furieri, Yang Zheng, and Maryam Kamgarpour · 2020
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Policy gradient methods for the noisy linear quadratic regulator over a finite horizon
Ben M Hambly, Renyuan Xu, and Huining Yang · 2020
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Derivative-free methods for policy optimization: Guarantees for linear quadratic systems
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L Bartlett, and Martin J Wainwright · 2020
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Stabilizing dynamical systems via policy gradient methods
Juan C Perdomo, Jack Umenberger, and Max Simchowitz · 2021
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John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz · 2015
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High-dimensional continuous control using generalized advantage estimation
John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel · 2015
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Global convergence of policy gradient methods for the linear quadratic regulator
Maryam Fazel, Rong Ge, Sham M Kakade, and Mehran Mesbahi · 2018
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Benjamin Gravell, Peyman Mohajerin Esfahani, and Tyler Summers · 2019
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Yingying Li, Yujie Tang, Runyu Zhang, and Na Li · 2019
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Yang Zheng, Yujie Tang, and Na Li · 2021
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Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, and Tamer Başar · 2021
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Bin Hu and Yang Zheng · 2022
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Globally convergent policy search over dynamic filters for output estimation
Jack Umenberger, Max Simchowitz, Juan C Perdomo, Kaiqing Zhang, and Russ Tedrake · 2022
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Receding-horizon policy gradient for linear robust control with fine-grained sample complexity
Xiangyuan Zhang, Bin Hu, and Tamer Başar · 2022
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Revisiting LQR control from the perspective of receding-horizon policy gradient
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