Fast planning through planning graph analysis

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Abstract

We introduce a new approach to planning in STRIPS-like domains based on constructing and analyzing 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 artificial 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 from the searches of other common planning methods, they provide a new perspective on the planning problem. © 1997 Elsevier Science B.V.

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APA

Blum, A. L., & Furst, M. L. (1997). Fast planning through planning graph analysis. Artificial Intelligence, 90(1–2), 281–300. https://doi.org/10.1016/s0004-3702(96)00047-1

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