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

Published: 03 September 2012 Publication History

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.

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    CUBE '12: Proceedings of the CUBE International Information Technology Conference
    September 2012
    879 pages
    ISBN:9781450311854
    DOI:10.1145/2381716
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    Published: 03 September 2012

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    Author Tags

    1. context free grammar
    2. evolutionary algorithms
    3. genetic algorithms
    4. language learning

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    • (2023)Improved Fracture Surface Analysis of Anticline Rocky Slopes Using a Modified AGA Approach: Feasibility and Effectiveness EvaluationSustainability10.3390/su1509745515:9(7455)Online publication date: 1-May-2023
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