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Towards a Reformulation Based Approach for Efficient Numeric Planning: Numeric Outer Entanglements

机译:迈向基于重构的有效数字规划方法:数字外部纠缠

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Restricting the search space has shown to be an effective approach for improving the performance of automated planning systems. A planner-independent technique for pruning the search space is domain and problem reformulation. Recently, Outer Entanglements, which are relations between planning operators and initial or goal predicates, have been introduced as a reformulation technique for eliminating potential undesirable instances of planning operators, and thus restricting the search space. Reformulation techniques, however, have been mainly applied in classical planning, although many real-world planning applications require to deal with numerical information. In this paper, we investigate the usefulness of reformulation approaches in planning with numerical fluents. In particular, we propose and extension of the notion of outer entanglements for handling numeric fluents. An empirical evaluation, which involves 150 instances from 5 domains, shows promising results.
机译:限制搜索空间已被证明是提高自动化规划系统性能的有效方法。用于修剪搜索空间的计划者的独立技术是域和问题重构。最近,已经引入了规划运营商与初始或目标谓词之间的关系,作为一种重构技术,以消除规划运营商的潜在不良情况,从而限制搜索空间。然而,重构技术主要应用于经典规划,尽管许多现实世界计划应用程序需要处理数值信息。在本文中,我们调查了规划数控规划方面的有用性。特别是,我们提出并延长了处理数值速率的外部纠缠的概念。涉及来自5个域的150例的经验评估显示了有希望的结果。

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