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Case-based Planning for Problems with Real-valued Fluents: Kernel Functions for Effective Plan Retrieval

机译:基于案例的实证流程问题的规划:有效计划检索的内核功能

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Case-based planning (CBP) re-uses existing plans as a starting point to solve new planning problems. In this work, we address CBP for planning in PDDL domains with real-valued fluents, that are essential to model real-world problems involving continuous resources. Specifically, we propose some new heuristic techniques for retrieving a plan from a library of existing plans that is promising for a new given planning problem, i.e., that can be efficiently adapted to solve the new problem. The effectiveness of these techniques, which derive much of their power from the use of the numerical information in the planning problem specification and in the library plans, is then evaluated by an experimental analysis.
机译:基于案例的规划(CBP)重新使用现有计划作为解决新规划问题的起点。在这项工作中,我们解决了CBP,以便在具有实质流销的PDDL域中进行计划,这对于模拟涉及持续资源的现实问题至关重要。具体来说,我们提出了一些新的启发式技术,用于从一个关于新的规划问题的现有计划的图书馆检索计划,即可以有效适应解决新问题。通过实验分析评估这些技术从使用规划问题规范和图书馆计划中使用数值信息的许多力量的有效性。

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