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

Anikó Ekárt; Steven Gustafson

doi:10.1007/978-3-540-24650-3_4

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

Anikó Ekárt, Steven Gustafson

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Chapter

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.

Original language	English
Title of host publication	Genetic programming
Subtitle of host publication	7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings
Editors	Maarten Keijzer, Una-May O’Reilly, Simon Lucas, Ernesto Costa, Terence Soule
Place of Publication	Berlin (DE)
Publisher	Springer
Pages	35-46
Number of pages	12
ISBN (Electronic)	978-3-540-24650-3
ISBN (Print)	978-3-540-21346-8
DOIs	https://doi.org/10.1007/978-3-540-24650-3_4
Publication status	Published - 1 Jan 2004
Event	7th European Conference - Coimbra, Portugal Duration: 5 Apr 2004 → 7 Apr 2004

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	3003
ISSN (Print)	0302-9743

Conference

Conference	7th European Conference
Abbreviated title	EuroGP 2004
Country/Territory	Portugal
City	Coimbra
Period	5/04/04 → 7/04/04

Access to Document

10.1007/978-3-540-24650-3_4

Cite this

Ekárt, A., & Gustafson, S. (2004). A data structure for improved gp analysis via efficient computation and visualisation of population measures. In M. Keijzer, U.-M. O’Reilly, S. Lucas, E. Costa, & T. Soule (Eds.), Genetic programming: 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings (pp. 35-46). (Lecture Notes in Computer Science ; Vol. 3003). Springer. https://doi.org/10.1007/978-3-540-24650-3_4

Ekárt, Anikó ; Gustafson, Steven. / A data structure for improved gp analysis via efficient computation and visualisation of population measures. Genetic programming: 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings. editor / Maarten Keijzer ; Una-May O’Reilly ; Simon Lucas ; Ernesto Costa ; Terence Soule. Berlin (DE) : Springer, 2004. pp. 35-46 (Lecture Notes in Computer Science ).

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Ekárt, A & Gustafson, S 2004, A data structure for improved gp analysis via efficient computation and visualisation of population measures. in M Keijzer, U-M O’Reilly, S Lucas, E Costa & T Soule (eds), Genetic programming: 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings. Lecture Notes in Computer Science , vol. 3003, Springer, Berlin (DE), pp. 35-46, 7th European Conference, Coimbra, Portugal, 5/04/04. https://doi.org/10.1007/978-3-540-24650-3_4

A data structure for improved gp analysis via efficient computation and visualisation of population measures. / Ekárt, Anikó; Gustafson, Steven.
Genetic programming: 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings. ed. / Maarten Keijzer; Una-May O’Reilly; Simon Lucas; Ernesto Costa; Terence Soule. Berlin (DE): Springer, 2004. p. 35-46 (Lecture Notes in Computer Science ; Vol. 3003).

Research output: Chapter in Book/Published conference output › Chapter

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AU - Ekárt, Anikó

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N2 - 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.

AB - 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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EP - 46

BT - Genetic programming

A2 - Keijzer, Maarten

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PB - Springer

CY - Berlin (DE)

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Ekárt A, Gustafson S. A data structure for improved gp analysis via efficient computation and visualisation of population measures. In Keijzer M, O’Reilly UM, Lucas S, Costa E, Soule T, editors, Genetic programming: 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings. Berlin (DE): Springer. 2004. p. 35-46. (Lecture Notes in Computer Science ). doi: 10.1007/978-3-540-24650-3_4

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

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