scientific article; zbMATH DE number 7626780

Publication date: 6 December 2022

Full work available at URL: https://arxiv.org/abs/2011.01364

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

system identification adaptive control safety reinforcement learning linear dynamical system uncertainty quantification exact asymptotics

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

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Least costly identification experiment for control
Iterated least squares in multiperiod control
Asymptotic distributions of regression and autoregression coefficients with martingale difference disturbances
Linear Thompson sampling revisited
Finite time identification in unstable linear systems
Asymptotically efficient adaptive control in stochastic regression models
Convergence and logarithm laws of self-tuning regulators
Input perturbations for adaptive control and learning
On the sample complexity of the linear quadratic regulator
Optimal experiment design for identification of ARX models with constrained output in non-Gaussian noise
Identification of ARX systems with non-stationary inputs -- asymptotic analysis with application to adaptive input design
On self tuning regulators
Adaptive control with the stochastic approximation algorithm: Geometry and convergence
Prediction Mean Squared Error for State Space Models with Estimated Parameters
Extended least squares and their applications to adaptive control and prediction in linear systems
The AAstrom-Wittenmark self-tuning regulator revisited and ELS-based adaptive trackers
On the discrete time algebraic Riccati equation
Optimality of Fast-Matching Algorithms for Random Networks With Applications to Structural Controllability
PANEL COINTEGRATION: ASYMPTOTIC AND FINITE SAMPLE PROPERTIES OF POOLED TIME SERIES TESTS WITH AN APPLICATION TO THE PPP HYPOTHESIS
Revisiting Ho–Kalman-Based System Identification: Robustness and Finite-Sample Analysis
Posterior Sampling-Based Reinforcement Learning for Control of Unknown Linear Systems
Adaptive Input Design for LTI Systems
The Kernel Recursive Least-Squares Algorithm
Least squares estimates in stochastic regression models with applications to identification and control of dynamic systems

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