Constraining Influence Diagram Structure by Generative Planning: An
  Application to the Optimization of Oil Spill Response
  This paper works through the optimization of a real world planning problem,
with a combination of a generative planning tool and an influence diagram
solver. The problem is taken from an existing application in the domain of oil
spill emergency response. The planning agent manages constraints that order
sets of feasible equipment employment actions. This is mapped at an
intermediate level of abstraction onto an influence diagram. In addition, the
planner can apply a surveillance operator that determines observability of the
state---the unknown trajectory of the oil. The uncertain world state and the
objective function properties are part of the influence diagram structure, but
not represented in the planning agent domain. By exploiting this structure
under the constraints generated by the planning agent, the influence diagram
solution complexity simplifies considerably, and an optimum solution to the
employment problem based on the objective function is found. Finding this
optimum is equivalent to the simultaneous evaluation of a range of plans. This
result is an example of bounded optimality, within the limitations of this
hybrid generative planner and influence diagram architecture.
