Bayesian ddLQR adds posterior uncertainty to the design, decomposing expected cost into certainty-equivalence plus variance terms, proving indirect-direct equivalence, and producing a data-length-independent SDP.
Certainty equivalence is efficient for linear quadratic control
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An online algorithm for zero-sum LQ games with unknown dynamics combines model estimation and surrogate selection to achieve regret bounds on policy convergence.
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An Online Learning Approach for Two-Player Zero-Sum Linear Quadratic Games
An online algorithm for zero-sum LQ games with unknown dynamics combines model estimation and surrogate selection to achieve regret bounds on policy convergence.