Iterative method of generating artificial context-free grammars

Abstract

Grammatical inference is a machine learning area, whose fundamentals are built around learning sets. At present, real-life data and examples from manually crafted grammars are used to test their learning performance. This paper aims to present a method of generating artificial context-free grammars with their optimal learning sets, which could be successfully applied as a benchmarking tool for empirical grammar inference methods.