Solving stochastic optimization models wit

In this paper we present a general single-agent stochastic dynamic optimization model that is capable of dealing with learning and with rational expectations. We obtain the solution by solving at every time step the rational expectations model and then applying existing optimization schemes to derive the optimal solution.