Dynamic optimization and optimal control problems form the backbone of numerous applications in engineering, economics and the natural sciences. These methodologies involve determining a time-varying ...

We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, ...