An investigation into the use of different search strategies with grammatical evolution

John O’Sullivan, Conor Ryan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present an investigation into the performance of Grammatical Evolution using a number of different search strategies, Simulated Annealing, Hill Climbing, Random Search and Genetic Algorithms. Comparative results on three different problems are examined. We analyse the nature of the search spaces presented by these problems and offer an explanation for the contrasting performance of each of the search strategies. Our results show that Genetic Algorithms provide a consistent level of performance across all three problems successfully coping with sensitivity of the system to discrete changes in the selection of productions from the associated grammar.

Original languageEnglish
Title of host publicationGenetic Programming - 5th European Conference, EuroGP 2002, Proceedings
EditorsJames A. Foster, Evelyne Lutton, Julian Miller, Conor Ryan, Andrea G.B. Tettamanzi
PublisherSpringer Verlag
Pages268-277
Number of pages10
ISBN (Print)9783540433781
DOIs
Publication statusPublished - 2002
Event5th European Conference on Genetic Programming, EuroGP 2002 - Kinsale, Ireland
Duration: 3 Apr 20025 Apr 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2278
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th European Conference on Genetic Programming, EuroGP 2002
Country/TerritoryIreland
CityKinsale
Period3/04/025/04/02

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