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Planning Based on Classification by Induction Graph

机译:基于归纳图分类的规划

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In Artificial Intelligence, planning refers to an area of research that proposes to develop systems that can automatically generate a result set, in the form of an integrated decision-making system through a formal procedure, known as plan. Instead of resorting to the scheduling algorithms to generate plans, it is proposed to operate the automatic learning by decision tree to optimize time. In this paper, we propose to build a classification model by induction graph from a learning sample containing plans that have an associated set of descriptors whose values change depending on each plan. This model will then operate for classifying new cases by assigning the appropriate plan
机译:在人工智能中,计划是指研究领域,该领域提议开发可以通过正式程序(称为计划)以集成决策系统的形式自动生成结果集的系统。代替使用调度算法来生成计划,建议通过决策树来操作自动学习以优化时间。在本文中,我们建议从包含计划的学习样本中通过归纳图构建分类模型,该计划包含具有一组关联的描述符,描述符的值根据每个计划而变化。然后,该模型将通过分配适当的计划来对新病例进行分类

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