Genetic algorithms: Concepts, issues and a case study of grammar induction

Hari Mohan Pandey*, Anurag Dixit, Deepti Mehrotra

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)peer-review

11 Citations (Scopus)

Abstract

This paper discusses a case study of grammar induction. Grammar induction is the process of learning grammar from a set of training data of the positive (S +) and negative (S -) strings. An algorithm has been designed and implemented for the induction of context free grammar (CFG). Special bit mask oriented data structures have been used to apply the crossover and mutation operations. The aim is to establish the applicability of the genetic algorithms (GAs) for different engineering problems. The paper lays a concrete foundation to formulating problems in the genetic algorithm framework. In addition, the basic principles of standard genetic algorithm, such as encoding techniques, selection techniques, operators (crossover and mutation), and the issues raised in the relevant literature have been discussed to establish the applicability of the genetic algorithm.

Original languageEnglish
Title of host publicationProceedings of the CUBE International Information Technology Conference, CUBE 2012
PublisherAssociation for Computing Machinery (ACM)
Pages263-271
Number of pages9
ISBN (Print)9781450311854
DOIs
Publication statusPublished - 19 Nov 2012
EventInternational Information Technology Conference, CUBE 2012 - Pune, Maharashtra, India
Duration: 3 Sept 20125 Sept 2012

Publication series

NameACM International Conference Proceeding Series

Conference

ConferenceInternational Information Technology Conference, CUBE 2012
Country/TerritoryIndia
CityPune, Maharashtra
Period3/09/125/09/12

Keywords

  • Context free grammar
  • Evolutionary algorithms
  • Genetic algorithms
  • Language learning

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