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arXiv · 2309.10142

Controlling Unknown Linear Dynamics with Almost Optimal Regret

Jacob Carruth·Maximilian F. Eggl·Charles Fefferman·Clarence W. Rowley
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Abstract

Here and in a companion paper, we consider a simple control problem in which the underlying dynamics depend on a parameter $a$ that is unknown and must be learned. In this paper, we assume that $a$ can be any real number and we do not assume that we have a prior belief about $a$. We seek a control strategy that minimizes a quantity called the regret. Given any $\varepsilon>0$, we produce a strategy that minimizes the regret to within a multiplicative factor of $(1+\varepsilon)$.

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Jacob Carruth, Maximilian F. Eggl, Charles Fefferman, Clarence W. Rowley. 2023-09-18. Controlling Unknown Linear Dynamics with Almost Optimal Regret. https://arxiv.org/abs/2309.10142

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