A Dynamic Programming Algorithm for Finding an Optimal Sequence of Informative Measurements
An informative measurement is the most efficient way to gain information about an unknown state.We present a first-principles derivation of a general-purpose dynamic programming algorithm that returns an optimal sequence of informative measurements by sequentially maximizing the entropy of possible measurement outcomes.This algorithm can be used by