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Evolving Stochastic Context-Free g rammars Using g enetic Algorithm

Evolving Stochastic Context-Free g rammars Using g enetic Algorithm
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Author(s): Anupam Shukla (National Institute of Technology, India) and Devesh Narayan (National Institute of Technology, India)
Copyright: 2007
Pages: 4
Source title: Managing Worldwide Operations and Communications with Information Technology
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-929-8.ch396
ISBN13: 9781599049298
EISBN13: 9781466665378

Abstract

The learning of stochastic context-free grammars from corpus using genetic algorithm is explored in this work. Minimum description length principle is used for deriving the fitness function of the genetic algorithm. Stochastic context-free grammars are evolved by optimizing the parameters of the covering grammars. I provide details of my fitness function for grammars and present the results of a number of experiments in learning grammars for a variety of languages.

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