使用遗传算法构建Greibach范式语法

Signals Pub Date : 2022-10-12 DOI:10.3390/signals3040042
Nikolaos P. Anastasopoulos, E. Dermatas
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引用次数: 0

摘要

在现代人工语言和自然语言技术中,使用正反两种语言实例对无上下文语法进行语法推理是最具挑战性的任务之一。最近,已经提出了几种结合各种技术的实现,通常包括Backus-Naur格式。在本文中,我们探索了一种基于Greibach范式及其特性的进化方法来实现语法推理,并在进化过程和相应的适应度估计中提出了新的解决方案。
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Building Greibach Normal Form Grammars Using Genetic Algorithms
Grammatical inference of context-free grammars using positive and negative language examples is among the most challenging task in modern artificial and natural language technology. Recently, several implementations combining various techniques, usually including the Backus–Naur form, have been proposed. In this paper, we explore a new implementation of grammatical inference using evolution methods focused on the Greibach normal form and exploiting its properties, and also propose new solutions both in the evolutionary processes and in the corresponding fitness estimation.
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CiteScore
3.20
自引率
0.00%
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0
审稿时长
11 weeks
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