Fast Planning Through Planning Graph Analysis

We introduce a new approach to planning in STRIPS-like domains based on constructing and analysing a compact structure we call a Planning Graph We describe a new planner, Graphplan, that uses this paradigm Graphplan always returns a shortest-possible partial-order plan, or states that no valid plan exists We provide empirical evidence in favor of this approach, showing that Graphplan outperforms the total-order planner, Prodigy, and the partial-order planner, UCPOP, on a variety of interesting natural and artif icial planning problems We also give empirical evidence that the plans produced by Graphplan are quite sensible Since searches made by this approach are fundamentally different f rom the searches of other common planning methods, they provide a new perspective on the planning problem