  We introduce a completely abstract dynamic programming framework in which
dynamic programs are sets of policy operators acting on a partially ordered
space. We provide an optimality theory based on high-level assumptions. We then
study symmetric and asymmetric relationships between dynamic programs, and show
how these relationships transmit optimality properties. Our formulation
includes and extends applications of dynamic programming across many fields.
