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Relating the Performance of  (Make Corrections)  
Partial-Order Planning AlgorithmstoDomainFeatures Craig A. Knoblock Qiang...



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Abstract: The AI planning field has a long history of introducing yet another search algorithm that is believed to be the best in all domains. Some recent examples are nonlin, tweak snlp.Inthis paper weshow, by directly comparing the above three planners, that the quest for an overall winner is doomed to fail. We first argue that these three planners differ in a varietyofways, including methods for termination check, causal-link protection, and subgoal selection. These differences entail... (Update)

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@misc{ algorithmstodomainfeatures-relating,
  author = "Partial-Order Planning Algorithmstodomainfeatures",
  title = "Relating the Performance of",
  url = "citeseer.ist.psu.edu/766045.html" }
Citations (may not include all citations):
451   Planning for conjunctive goals (context) - Chapman - 1987
251   Generating project networks (context) - Tate - 1977
82   Systematic nonlinear planning - McAllester, Rosenblitt - 1991
45   Commitment strategies in planning: A comparative analysis (context) - Minton, Bresina et al. - 1991
29   Multi-contributor causal structures for planning: A formaliz.. - Kambhampati - 1994
19   Partial-order planning: Evaluating possible efficiency gains (context) - Barrett, Weld - 1994
16   Refinement search as a unifying framework for analyzing plan.. - Kambhampati - 1994
8   Evaluating the tradeoffs in partial-order planning algorithm.. - Knoblock, Yang - 1994
4   Planning as refinement search: A unified framework for evalu.. (context) - Kambhampati, Knoblock et al. - 1994
2   the utility of systematicity: Understanding tradeoffs betwee.. (context) - Kambhampati - 1993

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