In “Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems” Ibrahimi, Javanmard, and Van Roy (2012) present a fast reinforcement learning solution for linear control systems problems with quadratic costs.  The problem is to minimize the total cost $\min_u \sum_{i=1}^T x_i^t Q x_i + u_i^t R u_i$ for the control system $x_{i+1} = A x_i + B u_i + w_i$ where $x\in R^j$ is the state of the system; $u\in R^k$ is the control; $Q, R, A,$ and $B$ are matrices; and $w_i\in R^j$ is a random multivariate normally distributed vector.

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