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On the implementation and evaluation of AbTweak
Qiang Yang, Josh D. Tenenberg, Steven Woods
Computational Intelligence 12(2), pages 307–330
May 1996
In this paper, we describe the implementation and evaluation of the AbTweakplanning system, a test bed for studying and teaching concepts in partial‐order planning, abstraction, and search control. We start by extending the hierarchical, precondition‐elimination abstraction of ABSTRIPS to partial‐order‐based, least‐commitment planners such as Tweak. The resulting system, AbTweak, illustrates the advantages of using abstraction to improve the efficiency of search. We show that by protecting a subset of abstract conditions achieved so far, and by imposing a bias on search toward deeper levels in a hierarchy, planning efficiency can be greatly improved. Finally, we relate AbTweakto other planning systems SNLP, ALPINE, and SIPE by exploring their similarities and differences.
