Managing Repetition in Grammar-Based Genetic Programming
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Title: | Managing Repetition in Grammar-Based Genetic Programming | Authors: | Nicolau, Miguel; Fenton, Michael | Permanent link: | http://hdl.handle.net/10197/8248 | Date: | 24-Jul-2016 | Online since: | 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. | Funding Details: | Science Foundation Ireland | Type of material: | Conference Publication | Publisher: | ACM | Copyright (published version): | 2016 ACM | Keywords: | Evolutionary algorithms; Genetic programming | DOI: | 10.1145/2908812.2908904 | Language: | en | Status of Item: | Peer reviewed | Is 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: | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ |
Appears in Collections: | Business Research Collection |
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