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Optimism-Based Adaptive Regulation of Linear-Quadratic Systems

https://doi.org/10.1109/tac.2020.2998952
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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User-Friendly Tail Bounds for Sums of Random Matrices
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Persistence of excitation in linear systems
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Asymptotically efficient adaptive allocation rules
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Asymptotically efficient adaptive control in stochastic regression models
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Finite time identification in unstable linear systems
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Input perturbations for adaptive control and learning
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On adaptive Linear–Quadratic regulators
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Convergence of adaptive control schemes using least-squares parameter estimates
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Achieving optimality in adaptive control: the "bet on the best" approach
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Dual effect, certainty equivalence, and separation in stochastic control
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Adaptive control with the stochastic approximation algorithm: Geometry and convergence
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Extended least squares and their applications to adaptive control and prediction in linear systems
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Finite-Time Adaptive Stabilization of Linear Systems
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Optimality of Fast-Matching Algorithms for Random Networks With Applications to Structural Controllability
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Parallel Recursive Algorithms in Asymptotically Efficient Adaptive Control of Linear Stochastic Systems
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Adaptive Linear Quadratic Gaussian Control: The Cost-Biased Approach Revisited
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Martingale Central Limit Theorems
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Least Squares Estimates in Stochastic Regression Models with Applications to Identification and Control of Dynamic Systems
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Persistence of Excitation in Linear Systems
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[untitled]
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Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems

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Asymptotic Normality of Cumulative Cost in Linear Quadratic Regulators
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Table of Contents
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2021 Index IEEE Transactions on Automatic Control Vol. 66
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Online Learning of the Kalman Filter With Logarithmic Regret
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Multiagent Online Source Seeking Using Bandit Algorithm
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Strong Consistency and Rate of Convergence of Switched Least Squares System Identification for Autonomous Markov Jump Linear Systems
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Online Actuator Selection and Controller Design for Linear Quadratic Regulation With an Unknown System Model
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Learn and Control While Switching: Guaranteed Stability and Sublinear Regret
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Scalable Regret for Learning to Control Network-Coupled Subsystems With Unknown Dynamics
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Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon
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Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting
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Thompson Sampling for Partially Observable Linear-Quadratic Control
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Hierarchical Robust Model Prediction Control for a Long-Endurance Unmanned Aerial Vehicle
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Regret Minimization in Partially Observable Linear Quadratic Control
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Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently
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Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
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Regret Bounds for LQ Adaptive Control Under Database Attacks (Extended Version)
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Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory
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SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory
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Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon
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Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
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Safe and Efficient Reinforcement Learning for decision-making in Autonomous Driving
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