Copertina

Domain Randomization is Sample Efficient for Linear Quadratic Control

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Fujinami, Tesshu, Lee, Bruce D., Matni, Nikolai, Pappas, George J.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Systems and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Policy Gradient for LQR with Domain Randomization
di: Fujinami, Tesshu, et al.
Pubblicazione: (2025)

Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with Model Misspecification
di: Lee, Bruce D., et al.
Pubblicazione: (2023)

Statistical Efficiency of Single- and Multi-step Models for Forecasting and Control
di: Somalwar, Anne, et al.
Pubblicazione: (2026)

Active Learning for Control-Oriented Identification of Nonlinear Systems
di: Lee, Bruce D., et al.
Pubblicazione: (2024)

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples
di: Zhang, Thomas T., et al.
Pubblicazione: (2024)

Learning with Imperfect Models: When Multi-step Prediction Mitigates Compounding Error
di: Somalwar, Anne, et al.
Pubblicazione: (2025)

Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control
di: Lee, Bruce D., et al.
Pubblicazione: (2024)

State space models, emergence, and ergodicity: How many parameters are needed for stable predictions?
di: Ziemann, Ingvar, et al.
Pubblicazione: (2024)

On Globally Optimal Stochastic Policy Gradient Methods for Domain Randomized LQR Synthesis
di: Nguyen-Le, Alex, et al.
Pubblicazione: (2026)

A Tutorial on the Non-Asymptotic Theory of System Identification
di: Ziemann, Ingvar, et al.
Pubblicazione: (2023)

The Fragility of Learning LQG Controllers
di: Lee, Bruce D., et al.
Pubblicazione: (2026)

Closed-loop Analysis of ADMM-based Suboptimal Linear Model Predictive Control
di: Srikanthan, Anusha, et al.
Pubblicazione: (2024)

A Quantitative Framework for Navigating Controller Design Tradeoffs under Computational Constraints
di: Verhoek, Chris, et al.
Pubblicazione: (2026)

Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
di: Zhang, Thomas T. C. K., et al.
Pubblicazione: (2023)

Single Trajectory Conformal Prediction
di: Lee, Brian, et al.
Pubblicazione: (2024)

Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic Learning
di: Yang, Fengjun, et al.
Pubblicazione: (2024)

Scalable Distributed Nonlinear Control Under Flatness-Preserving Coupling
di: Yang, Fengjun, et al.
Pubblicazione: (2025)

Verification of Sequential Convex Programming for Parametric Non-convex Optimization
di: Sambharya, Rajiv, et al.
Pubblicazione: (2025)

Towards a Theory of Control Architecture: A quantitative framework for layered multi-rate control
di: Matni, Nikolai, et al.
Pubblicazione: (2024)

Layered Multirate Control of Constrained Linear Systems
di: Stamouli, Charis, et al.
Pubblicazione: (2025)

Learning Flatness-Preserving Residuals for Pure-Feedback Systems
di: Yang, Fengjun, et al.
Pubblicazione: (2025)

Learning Acceleration Algorithms for Fast Parametric Convex Optimization with Certified Robustness
di: Sambharya, Rajiv, et al.
Pubblicazione: (2025)

An Efficient Data-Driven Framework for Linear Quadratic Output Feedback Control
di: Xie, Jun, et al.
Pubblicazione: (2025)

Reactive Temporal Logic-based Planning and Control for Interactive Robotic Tasks
di: Nawaz, Farhad, et al.
Pubblicazione: (2024)

Quad-LCD: Layered Control Decomposition Enables Actuator-Feasible Quadrotor Trajectory Planning
di: Srikanthan, Anusha, et al.
Pubblicazione: (2025)

Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method
di: Stamouli, Charis, et al.
Pubblicazione: (2024)

Conformal Prediction Regions for Time Series using Linear Complementarity Programming
di: Cleaveland, Matthew, et al.
Pubblicazione: (2023)

Optimality of Linear Policies in Distributionally Robust Linear Quadratic Control
di: Taşkesen, Bahar, et al.
Pubblicazione: (2025)

Layered Control of Partially Observed Stochastic Systems
di: Stamouli, Charis, et al.
Pubblicazione: (2026)

Action Chunking and Exploratory Data Collection Yield Exponential Improvements in Behavior Cloning for Continuous Control
di: Zhang, Thomas T., et al.
Pubblicazione: (2025)

Safe Planning in Interactive Environments via Iterative Policy Updates and Adversarially Robust Conformal Prediction
di: Mirzaeedodangeh, Omid, et al.
Pubblicazione: (2025)

Learning Complex Motion Plans using Neural ODEs with Safety and Stability Guarantees
di: Nawaz, Farhad, et al.
Pubblicazione: (2023)

Robustness and Consistency in Linear Quadratic Control with Untrusted Predictions
di: Li, Tongxin, et al.
Pubblicazione: (2021)

On the Global Optimality of Linear Policies for Sinkhorn Distributionally Robust Linear Quadratic Control
di: Cescon, Riccardo, et al.
Pubblicazione: (2025)

Deep Equivariant Multi-Agent Control Barrier Functions
di: Bousias, Nikolaos, et al.
Pubblicazione: (2025)

Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems
di: Zhang, Hanli, et al.
Pubblicazione: (2024)

Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations
di: Lindemann, Lars, et al.
Pubblicazione: (2021)

Quadratic Optimal Control of Graphon Q-noise Linear Systems
di: Dunyak, Alex, et al.
Pubblicazione: (2024)

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

Deception Against Data-Driven Linear-Quadratic Control
di: Fotiadis, Filippos, et al.
Pubblicazione: (2025)