The Smoothed Linear Program for Approximate Dynamic Programming
We present a novel linear program for the approximation of the dynamic programming value function in high-dimensional stochastic control problems. LP approaches to approximate DP naturally restrict attention to approximations that, depending on the context, are upper or lower bounds to the optimal value function. Our program -- the `smoothed LP' -- relaxes this restriction in an appropriate fashion while remaining computationally tractable. Doing so appears to have several advantages: o We demonstrate superior bounds on the quality of approximation…