  We consider a linear-quadratic optimal control problem in discrete time with
distributional ambiguity, where the random cumulative quadratic cost is
assessed via the Conditional Value-at-Risk (CVaR) functional. We take steps
toward deriving a scalable value iteration algorithm to upper-bound the
solution to this problem. A remarkable finding is that the value functions
depend on positive definite matrices, which are computed by a Riccati-like
recursion.
