Cover Image

Policy Gradient Methods for Discrete Time Linear Quadratic Regulator With Random Parameters

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Li, Deyue
Format:	Preprint
Published:	2023
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators
by: Han, Yinbin, et al.
Published: (2023)

Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods
by: Carmona, René, et al.
Published: (2019)

Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for Model-free LQR
by: Toso, Leonardo F., et al.
Published: (2024)

Reinforcement Learning for a Discrete-Time Linear-Quadratic Control Problem with an Application
by: Li, Lucky
Published: (2024)

Accelerated Optimization Landscape of Linear-Quadratic Regulator
by: Feng, Lechen, et al.
Published: (2023)

Fast Policy Learning for Linear Quadratic Control with Entropy Regularization
by: Guo, Xin, et al.
Published: (2023)

Tsallis Entropy Regularization for Linearly Solvable MDP and Linear Quadratic Regulator
by: Hashizume, Yota, et al.
Published: (2024)

Learning Decentralized Linear Quadratic Regulators with $\sqrt{T}$ Regret
by: Ye, Lintao, et al.
Published: (2022)

Asynchronous Parallel Policy Gradient Methods for the Linear Quadratic Regulator
by: Sha, Xingyu, et al.
Published: (2024)

Regret Bounds for Episodic Risk-Sensitive Linear Quadratic Regulator
by: Xu, Wenhao, et al.
Published: (2024)

Sample Complexity of Linear Quadratic Regulator Without Initial Stability
by: Moghaddam, Amirreza Neshaei, et al.
Published: (2025)

Elementary Analysis of Policy Gradient Methods
by: Liu, Jiacai, et al.
Published: (2024)

Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens
by: Moghaddam, Amirreza Neshaei, et al.
Published: (2024)

Quadratic Gradient: A Unified Framework Bridging Gradient Descent and Newton-Type Methods by Synthesizing Hessians and Gradients
by: Chiang, John
Published: (2022)

Model-Free Learning for the Linear Quadratic Regulator over Rate-Limited Channels
by: Ye, Lintao, et al.
Published: (2024)

Rate-Optimal Regret for the Safe Learning-based Control of the Constrained Linear Quadratic Regulator
by: Hutchinson, Spencer, et al.
Published: (2026)

Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
by: Cayci, Semih, et al.
Published: (2021)

Optimization of Discrete Parameters Using the Adaptive Gradient Method and Directed Evolution
by: Beinarovich, Andrei, et al.
Published: (2024)

Gradient Dominance in the Linear Quadratic Regulator: A Unified Analysis for Continuous-Time and Discrete-Time Systems
by: Watanabe, Yuto, et al.
Published: (2026)

Global Convergence of Policy Gradient Methods for ReLU Controllers in Linear Quadratic Regulation
by: Rodriguez-Gil, Jhojan A., et al.
Published: (2026)

Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems
by: Shin, Sungho, et al.
Published: (2022)

Towards Simple and Provable Parameter-Free Adaptive Gradient Methods
by: Tao, Yuanzhe, et al.
Published: (2024)

Mutual Information Optimal Control of Discrete-Time Linear Systems
by: Enami, Shoju, et al.
Published: (2025)

Analysis of On-policy Policy Gradient Methods under the Distribution Mismatch
by: Wang, Weizhen, et al.
Published: (2025)

Reheated Gradient-based Discrete Sampling for Combinatorial Optimization
by: Li, Muheng, et al.
Published: (2025)

DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
by: Khaled, Ahmed, et al.
Published: (2023)

Interpreting Adaptive Gradient Methods by Parameter Scaling for Learning-Rate-Free Optimization
by: Suh, Min-Kook, et al.
Published: (2024)

Fixed Horizon Linear Quadratic Covariance Steering in Continuous Time with Hilbert-Schmidt Terminal Cost
by: Sial, Tushar, et al.
Published: (2025)

Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods
by: Klein, Sara, et al.
Published: (2023)

Model-Free Output Feedback Stabilization via Policy Gradient Methods
by: Zhang, Ankang, et al.
Published: (2026)

Convergence for Discrete Parameter Update Schemes
by: Wilson, Paul, et al.
Published: (2025)

Regret Lower Bounds for Learning Linear Quadratic Gaussian Systems
by: Ziemann, Ingvar, et al.
Published: (2022)

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
by: Ding, Dongsheng, et al.
Published: (2023)

Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
by: Ziyin, Liu, et al.
Published: (2024)

Generalized Continuous-Time Models for Nesterov's Accelerated Gradient Methods
by: Park, Chanwoong, et al.
Published: (2024)

On the Effectiveness of the z-Transform Method in Quadratic Optimization
by: Bach, Francis
Published: (2025)

Gradient Descent Converges Linearly to Flatter Minima than Gradient Flow in Shallow Linear Networks
by: Beneventano, Pierfrancesco, et al.
Published: (2025)

Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning
by: Zeng, Sihan, et al.
Published: (2024)

Nonconvex Optimization Framework for Group-Sparse Feedback Linear-Quadratic Optimal Control: Penalty Approach
by: Feng, Lechen, et al.
Published: (2025)

Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem
by: Chakrabarti, Kushal, et al.
Published: (2021)