This description of stochastic dynamical optimization models is intended to exhibit some of the connections between various formulations that have appeared in the literature, and indicate some of the difficulties that must be overcome when trying to adapt solution methods that have been successfully applied to one class of problems to an apparently related but different class of problems. The emphasis is on solvable models. The authors begin with the least dynamical versions of stochastic optimization models, one- and two-stage models then consider discrete time models, and conclude with continuous time models
