从一般到具体的霍恩从句的正例学习

I. Stahl, B. Tausend, R. Wirth
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引用次数: 3

摘要

作者描述了一种方法来学习的析取概念表示为霍恩子句在一般到具体的方式。他们已经确定了一类受限制的霍恩分句,这些分句的正面例子足以检测出过于笼统的分句。该方法在一个名为INDICO的系统中开发和实现,从示例中提取尽可能多的约束信息,从而可以有效地搜索可能解的空间。INDICO的工作分为三个步骤。首先,确定目标谓词的参数类型。其次,对示例集进行分区,并为每个分区确定子句头,该子句头涵盖分区中的所有示例。第三,通过在子句的主体上添加文字(包括新发明的文字)来对子句进行专门化,直到定义正确为止。给出了一些实验结果。
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General-to-specific learning of Horn clauses from positive examples
The authors describe a method for learning disjunctive concepts represented as Horn clauses in a general-to-specific manner. They have identified a restricted class of Horn clauses for which positive examples are sufficient to detect overgeneral clauses. The method, developed and implemented in a system called INDICO, extracts as much constraining information as possible from the examples, such that the space of possible solutions can be searched efficiently. INDICO works in three steps. First, the argument types of the target predicate are determined. Second, the example set is partitioned and for each partition a clause head is determined which covers all the examples in the partition. Third, the clauses are specialized by adding literals, including newly invented ones, to their body until the definition is correct. Some experimental results are presented.<>
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Neural clustering algorithms for classification and pre-placement of VLSI cells General-to-specific learning of Horn clauses from positive examples Minimization of NAND circuits by rewriting-rules heuristic A generalized stochastic Petri net model of Multibus II Activation of connections to accelerate the learning in recurrent back-propagation
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