Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret

Alon Cohen; Tomer Koren; Yishay Mansour

Learning Linear-Quadratic Regulators Efficiently with only sqrt{T} Regret

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arxiv 1902.06223 v2 pith:EIEBSFFO submitted 2019-02-17 cs.LG stat.ML

Learning Linear-Quadratic Regulators Efficiently with only sqrt{T} Regret

Alon Cohen , Tomer Koren , Yishay Mansour This is my paper

classification cs.LG stat.ML

keywords learningregretsqrtabbasi-yadkorialgorithmcomputationally-efficientcontroldean

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We present the first computationally-efficient algorithm with $\widetilde O(\sqrt{T})$ regret for learning in Linear Quadratic Control systems with unknown dynamics. By that, we resolve an open question of Abbasi-Yadkori and Szepesv\'ari (2011) and Dean, Mania, Matni, Recht, and Tu (2018).

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Proposes a regret-minimizing algorithm for safe mode switching in unknown-dynamics LQR that achieves expected regret O(|M|^{1/4} n_s^{3/4} + n_m) under infinite mode visits.