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On the Hardness of Planning Problems with Simple Causal Graphs

机译:简单因果图规划问题的难点

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We present three new complexity results for classes of planning problems with simple causal graphs. First, we describe a polynomial time algorithm that uses macros to generate plans for a class of planning problems with binary state variables and acyclic causal graphs. This implies that plan generation may not be intractable just because a planning problem has exponential length solution. We also prove that the problem of plan existence for planning problems with multi-valued variables and chain causal graphs is NP-hard. Finally, we show that plan existence for planning problems with binary state variables and polytree causal graphs is NP-complete.
机译:对于带有简单因果图的规划问题,我们提出了三种新的复杂度结果。首先,我们描述一种多项式时间算法,该算法使用宏为具有二进制状态变量和非循环因果图的一类规划问题生成计划。这意味着仅仅因为计划问题具有指数长度的解决方案,计划的生成就可能难以解决。我们还证明,对于具有多值变量和链因果图的计划问题,计划存在的问题是NP-难的。最后,我们证明了针对具有二元状态变量和多树因果图的规划问题的规划存在是NP完全的。

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