On the Linear Convergence of Random Search for Discrete-Time LQR
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Mahdi Soltanolkotabi | Hesameddin Mohammadi | Mihailo R. Jovanović | M. Soltanolkotabi | M. Jovanović | Hesameddin Mohammadi
[1] Mahdi Soltanolkotabi,et al. Random search for learning the linear quadratic regulator , 2020, 2020 American Control Conference (ACC).
[2] Tamer Basar,et al. Policy Optimization for H2 Linear Control with H∞ Robustness Guarantee: Implicit Regularization and Global Convergence , 2020, L4DC.
[3] B. Anderson,et al. Optimal control: linear quadratic methods , 1990 .
[4] Bin Hu,et al. Convergence Guarantees of Policy Optimization Methods for Markovian Jump Linear Systems , 2020, 2020 American Control Conference (ACC).
[5] Armin Zare,et al. Convergence and sample complexity of gradient methods for the model-free linear quadratic regulator problem , 2019, ArXiv.
[6] Karl Mårtensson,et al. Gradient Methods for Large-Scale and Distributed Linear Quadratic Control , 2012 .
[7] Benjamin Recht,et al. Simple random search provides a competitive approach to reinforcement learning , 2018, ArXiv.
[8] Sham M. Kakade,et al. Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator , 2018, ICML.
[9] Roman Vershynin,et al. High-Dimensional Probability , 2018 .
[10] M. Rudelson,et al. Hanson-Wright inequality and sub-gaussian concentration , 2013 .
[11] Mahdi Soltanolkotabi,et al. Global exponential convergence of gradient methods over the nonconvex landscape of the linear quadratic regulator , 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).
[12] Martin J. Wainwright,et al. Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems , 2018, AISTATS.
[13] Martin J. Wainwright,et al. Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations , 2013, IEEE Transactions on Information Theory.
[14] R. Bellman,et al. The Riccati Equation , 1986 .
[15] G. Hewer. An iterative technique for the computation of the steady state gains for the discrete optimal regulator , 1971 .
[16] Benjamin Recht,et al. A Tour of Reinforcement Learning: The View from Continuous Control , 2018, Annu. Rev. Control. Robotics Auton. Syst..
[17] Fu Lin,et al. Design of Optimal Sparse Feedback Gains via the Alternating Direction Method of Multipliers , 2011, IEEE Transactions on Automatic Control.
[18] Mehran Mesbahi,et al. LQR through the Lens of First Order Methods: Discrete-time Case , 2019, ArXiv.
[19] Mark W. Schmidt,et al. Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition , 2016, ECML/PKDD.