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具有中间条件和效果的符号模式时间数字规划

Symbolic Pattern Temporal Numeric Planning with Intermediate Conditions and Effects

Matteo Cardellini, Enrico Giunchiglia

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Under review at the Artificial Intelligence Journal
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AI总结：

本文提出了一种扩展的符号模式规划方法，用于处理具有中间条件和效果的时间规划问题，实验显示其在多个领域表现优异。

摘要：

最近，一种符号模式规划（SPP）方法被提出用于数值规划，其中模式（即有限个动作的序列）建议动作之间的因果顺序。然后将模式编码为SMT公式，其模型对应于有效的计划。如果模式的建议不准确且无法找到有效的计划，模式将被扩展，直到其中包含有效计划中动作的因果顺序，使该方法变得完整。在本文中，我们扩展了SPP方法以应用于具有中间条件和效果（ICEs）片段的时间规划，其中（i）动作是持续性的（因此可以重叠时间）且具有可以在动作执行过程中的任何时间检查/应用的条件/效果，且（ii）可以指定计划中必须在特定时间检查/应用的条件/效果。实验结果表明，我们的SPP规划器Patty（i）在大多数没有ICEs的时间域中优于文献中的所有其他规划器，（ii）在具有ICEs的文献域中与最先进的搜索规划器取得可比结果，（iii）在基于现实世界应用的新域中优于相同的规划器。

英文摘要：

Recently, a Symbolic Pattern Planning (SPP) approach was proposed for numeric planning where a pattern (i.e., a finite sequence of actions) suggests a causal order between actions. The pattern is then encoded in a SMT formula whose models correspond to valid plans. If the suggestion by the pattern is inaccurate and no valid plan can be found, the pattern is extended until it contains the causal order of actions in a valid plan, making the approach complete. In this paper, we extend the SPP approach to the temporal planning with Intermediate Conditions and Effects (ICEs) fragment, where $(i)$ actions are durative (and thus can overlap over time) and have conditions/effects which can be checked/applied at any time during an action's execution, and $(ii)$ one can specify plan's conditions/effects that must be checked/applied at specific times during the plan execution. Experimental results show that our SPP planner Patty $(i)$ outperforms all other planners in the literature in the majority of temporal domains without ICEs, $(ii)$ obtains comparable results with the SoTA search planner for ICS in literature domains with ICEs, and $(iii)$ outperforms the same planner in a novel domain based on a real-world application.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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