Markov Decision Processes with Exogenous Variables
Abstract
I present two algorithms for solving dynamic programs with exogenous variables: endogenous value iteration and endogenous policy iteration. These algorithms are always at least as fast as relative value iteration and relative policy iteration, and they are faster when the endogenous variables converge to their stationary distributions sooner than the exogenous variables.
This paper was accepted by Yinyu Ye, optimization.

