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Managing Repetition in Grammar-Based Genetic Programming
Author(s)
Date Issued
2016-07-24
Date Available
2017-01-04T10:14:36Z
Abstract
Grammar-based Genetic Programming systems are capable of generating identical phenotypic solutions, either by creating repeated genotypic representations, or from distinct genotypes, through their many-to-one mapping process. Furthermore, their initialisation process can generate a high number of duplicate individuals, while traditional variation and replacement operators can permit multiple individuals to percolate through generations unchanged. This can lead to a high number of phenotypically identical individuals within a population. This study investigates the frequency and effect of such duplicate individuals on a suite of benchmark problems. Both Grammatical Evolution and the CFG-GP systems are examined. Experimental evidence suggests that these useless evaluations can be instead be used either to speed-up the evolutionary process, or to delay convergence.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2016 ACM
Language
English
Status of Item
Peer reviewed
Part of
Friedrich, T. (ed.). Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion
Conference Details
Genetic and Evolutionary Computation - GECCO 2016, Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20-24, 2016, Proceedings, July, 2016
This item is made available under a Creative Commons License
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