在规划中挖掘有用的宏观动作

2016 Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR) Pub Date : 2016-09-01 DOI:10.1109/ICAIPR.2016.7585227

Sandra Castellanos-Paez, D. Pellier, H. Fiorino, S. Pesty

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引用次数: 1

摘要

近年来，规划工作取得了重大进展。在扩大计划综合的各种方法中，宏观行动的使用得到了广泛的探索。作为开发在线宏动作学习解决方案的第一步，我们提出了一种基于数据挖掘技术的算法来识别有用的宏动作。这些学习到的宏观行为在规划搜索中的整合比六个经典规划基准有了显著的改进。

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Mining useful macro-actions in planning

Planning has achieved significant progress in recent years. Among the various approaches to scale up plan synthesis, the use of macro-actions has been widely explored. As a first stage towards the development of a solution to learn on-line macro-actions, we propose an algorithm to identify useful macroactions based on data mining techniques. The integration in the planning search of these learned macro-actions shows significant improvements over six classical planning benchmarks.

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2016 Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR)

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