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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
Keywords:
Information Science Reference
/
IT Research & Theory
/
IT Research and Theory
/
Library & Information Science
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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