An algorithm for constrained stochastic LQR achieves tilde O of square root T regret and chance constraint satisfaction via SDP-based optimistic policies scaled for safety.
Then, we show thattr(Σs) ≤ν for all s∈ [τk+1 − 1]
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Rate-Optimal Regret for the Safe Learning-based Control of the Constrained Linear Quadratic Regulator
An algorithm for constrained stochastic LQR achieves tilde O of square root T regret and chance constraint satisfaction via SDP-based optimistic policies scaled for safety.