Deterministic stochastic optimal control

This paper approaches optimal control problems for discrete-time controlled Markov processes by representing the value of the problem in a dual Lagrangian form; the value is expressed as an inm um over a family of Lagrangian martingales of an expectation of a pathwise supremum of the objective adjusted by the Lagrangian martingale term. This representation opens up the possibility of numerical methods based on Monte Carlo simulation which may be advantageous in high-dimensional problems, or in problems with complicated constraints.