Learning the Scope of Applicability for Task Planning Knowledge in Experience-Based Planning Domains
Learning the Scope of Applicability for Task Planning Knowledge in Experience-Based Planning Domains
复制标题
了解基于经验的规划领域中任务规划知识的适用范围
DOI：
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发表时间：
2019
期刊：
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通讯作者：
A. Pinho
中科院分区：
文献类型：
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作者：
V. Mokhtari;R. Manevich;L. Lopes;A. Pinho
基于经验的规划域（EBPD）已经被提出来通过从经验中学习来改进问题解决。他们依赖于获取和使用任务知识，即，活动模式，用于为一类任务中的问题实例生成解决方案。使用三值逻辑分析（TVLA），我们扩展我们以前的工作，产生一组条件，确定活动模式的适用范围。推断的范围是一组潜在无界问题的抽象表示，以3值逻辑结构的形式，用于测试各个活动模式对解决不同任务问题的适用性。我们验证了这项工作的两个经典的规划域和模拟PR2的露台。
Experience-based planning domains (EBPDs) have been proposed to improve problem solving by learning from experience. They rely on acquiring and using task knowledge, i.e., activity schemata, for generating solutions to problem instances in a class of tasks. Using Three-Valued Logic Analysis (TVLA), we extend our previous work to generate a set of conditions that determine the scope of applicability of an activity schema. The inferred scope is an abstract representation of a potentially unbounded set of problems, in the form of a 3-valued logical structure, which is used to test the applicability of the respective activity schema for solving different task problems. We validate this work on two classical planning domains and a simulated PR2 in Gazebo.