Solving POMDPs by Searching in Policy Space
  Most algorithms for solving POMDPs iteratively improve a value function that
implicitly represents a policy and are said to search in value function space.
This paper presents an approach to solving POMDPs that represents a policy
explicitly as a finite-state controller and iteratively improves the controller
by search in policy space. Two related algorithms illustrate this approach. The
first is a policy iteration algorithm that can outperform value iteration in
solving infinitehorizon POMDPs. It provides the foundation for a new heuristic
search algorithm that promises further speedup by focusing computational effort
on regions of the problem space that are reachable, or likely to be reached,
from a start state.
