Heuristics for Cost-Optimal Classical Planning Based on Linear Programming
Heuristics for Cost-Optimal Classical Planning Based on Linear Programming
复制标题
基于线性规划的成本最优经典规划启发法
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Blai Bonet
中科院分区：
文献类型：
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作者：
F. Pommerening;Gabriele Röger;M. Helmert;Blai Bonet
成本最佳计划的许多启发式方法基于线性编程。我们通过一个通用框架来涵盖这种类型的几种有趣的启发式方法，该框架可以修复线性程序的目标函数。在框架内，可以将不同启发式方法的约束结合在一个启发式估计中，以主导组件启发式方法的最大值。可以根据其约束来比较该框架的不同启发式方法。我们介绍了有关现有启发式方法与实验结果之间关系的理论结果，这些结果证明了所提出的框架的潜力。
Many heuristics for cost-optimal planning are based on linear programming. We cover several interesting heuristics of this type by a common framework that fixes the objective function of the linear program. Within the framework, constraints from different heuristics can be combined in one heuristic estimate which dominates the maximum of the component heuristics. Different heuristics of the framework can be compared on the basis of their constraints. We present theoretical results on the relation between existing heuristics and experimental results that demonstrate the potential of the proposed framework.