A data structure for improved gp analysis via efficient computation and visualisation of population measures

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Abstract

Population measures for genetic programs are defined and analysed in an attempt to better understand the behaviour of genetic programming. Some measures are simple, but do not provide sufficient insight. The more meaningful ones are complex and take extra computation time. Here we present a unified view on the computation of population measures through an information hypertree (iTree). The iTree allows for a unified and efficient calculation of population measures via a basic tree traversal.

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Publication date1 Jan 2004
Publication titleGenetic programming : 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings
EditorsMaarten Keijzer, Una-May O’Reilly, Simon Lucas, Ernesto Costa, Terence Soule
Place of PublicationBerlin (DE)
PublisherSpringer
Pages35-46
Number of pages12
ISBN (Electronic)978-3-540-24650-3
ISBN (Print)978-3-540-21346-8
Original languageEnglish
Event7th European Conference - Coimbra, Portugal

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume3003
ISSN (Print)0302-9743

Conference

Conference7th European Conference
Abbreviated titleEuroGP 2004
CountryPortugal
CityCoimbra
Period5/04/047/04/04

DOI

Employable Graduates; Exploitable Research

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