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This paper works through the optimization of a real world planning problem,with a combination of a generative planning tool and an influence diagramsolver. The problem is taken from an existing application in the domain of oilspill emergency response. The planning agent manages constraints that ordersets of feasible equipment employment actions. This is mapped at anintermediate level of abstraction onto an influence diagram. In addition, theplanner can apply a surveillance operator that determines observability of thestate---the unknown trajectory of the oil. The uncertain world state and theobjective function properties are part of the influence diagram structure, butnot represented in the planning agent domain. By exploiting this structureunder the constraints generated by the planning agent, the influence diagramsolution complexity simplifies considerably, and an optimum solution to theemployment problem based on the objective function is found. Finding thisoptimum is equivalent to the simultaneous evaluation of a range of plans. Thisresult is an example of bounded optimality, within the limitations of thishybrid generative planner and influence diagram architecture.

Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response