基于被动学习和遗传算法的语法推理

Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI:10.1145/3310986.3311033

P. Grachev

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引用次数: 0

摘要

确定性有限自动机的数学模型具有广泛的应用潜力，例如在控制系统中。其中一些系统不是微不足道的，只能根据形式语言理论来定义。本文提出了一种新的语法推理模型，即由一组正反例合成一个确定性有限自动机。我们给出了在各种复杂形式语法上测试开发模型的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Grammar Inference Based on Passive Learning and Genetic Algorithm

The mathematical model of a deterministic finite automaton has a wide potential of application, for instance, in control systems. Some of that systems are not trivial and can be defined only in terms of formal language theory. In this paper, we propose a new model for grammar inference, i.e. synthesizing of a deterministic finite automaton by a list of positive and negative examples. We present the results of testing developed model on formal grammars of various complexity.

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Proceedings of the 3rd International Conference on Machine Learning and Soft Computing

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