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Explanation-Based Acquisition of Planning Operators

机译:基于解释的计划运营商收购

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摘要

Classical planning algorithms require that their operators be simple in order for planning to be tractable. However, the complexities of real world domains suggest that, in order to be accurate, planning operators must be complex. We demonstrate how, by taking advantage of background knowledge and the distribution of planning problems encountered, it is possible to automatically construct planning operators that are both reliable and succinct. The acquired operator is an encapsulated control loop that is specialized to best fit observed world behavior. Succinctness is achieved by publishing to the planner only those conditions required to succeed over the estimated distribution of problems. We demonstrate the acquisition of a context-appropriate "take-off" operator that can successfully control a complex flight simulator.
机译:经典的计划算法要求操作员必须简单才能使计划易于处理。但是,现实世界域的复杂性表明,为了准确起见,规划运营商必须很复杂。我们演示了如何利用背景知识和所遇到的计划问题的分布来自动构造可靠且简洁的计划运营商。获得的运算符是一个封装的控制循环,专门用于最适合观察到的世界行为。通过向计划者仅发布成功解决估计的问题分布所需的条件,可以达到简洁。我们演示了如何获取上下文相关的“起飞”运营商,该运营商可以成功控制复杂的飞行模拟器。

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