Article

Resource-limited genetic programming: the dynamic approach

Authors:

Ernesto CostaAuthors Info & Claims

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

Pages 1673 - 1680

https://doi.org/10.1145/1068009.1068290

Published: 25 June 2005 Publication History

Abstract

Resource-Limited Genetic Programming is a bloat control technique that imposes a single limit on the total amount of resources available to the entire population, where resources are tree nodes or code lines. We elaborate on this recent concept, introducing a dynamic approach to managing the amount of resources available for each generation. Initially low, this amount is increased only if it results in better population fitness. We compare the dynamic approach to the static method where a constant amount of resources is available throughout the run, and with the most traditional usage of a depth limit at the individual level. The dynamic approach does not impair performance on the Symbolic Regression of the quartic polynomial, and achieves excellent results on the Santa Fe Artificial Ant problem, obtaining the same fitness with only a small percentage of the computational effort demanded by the other techniques.

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Cited By

Farinati DVanneschi L(2024)A survey on dynamic populations in bio-inspired algorithmsGenetic Programming and Evolvable Machines10.1007/s10710-024-09492-425:2Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10710-024-09492-4
Silva SDignum SVanneschi L(2012)Operator equalisation for bloat free genetic programming and a survey of bloat control methodsGenetic Programming and Evolvable Machines10.1007/s10710-011-9150-513:2(197-238)Online publication date: 1-Jun-2012
https://dl.acm.org/doi/10.1007/s10710-011-9150-5
Costa EPozo AVergilio S(2010)A Genetic Programming Approach for Software Reliability ModelingIEEE Transactions on Reliability10.1109/TR.2010.204075959:1(222-230)Online publication date: Mar-2010
https://doi.org/10.1109/TR.2010.2040759
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Index Terms

Resource-limited genetic programming: the dynamic approach
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence

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cover image ACM Conferences

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

June 2005

2272 pages

ISBN:1595930108

DOI:10.1145/1068009

Editor:
Hans-Georg Beyer
Vorarlberg University of Applied Sciences, Austria
,
General Chair:
Una-May O'Reilly
CSAIL, MIT

Copyright © 2005 ACM.

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Publication History

Published: 25 June 2005

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GECCO05: Genetic and Evolutionary Computation Conference

June 25 - 29, 2005

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Farinati DVanneschi L(2024)A survey on dynamic populations in bio-inspired algorithmsGenetic Programming and Evolvable Machines10.1007/s10710-024-09492-425:2Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10710-024-09492-4
Silva SDignum SVanneschi L(2012)Operator equalisation for bloat free genetic programming and a survey of bloat control methodsGenetic Programming and Evolvable Machines10.1007/s10710-011-9150-513:2(197-238)Online publication date: 1-Jun-2012
https://dl.acm.org/doi/10.1007/s10710-011-9150-5
Costa EPozo AVergilio S(2010)A Genetic Programming Approach for Software Reliability ModelingIEEE Transactions on Reliability10.1109/TR.2010.204075959:1(222-230)Online publication date: Mar-2010
https://doi.org/10.1109/TR.2010.2040759
Whigham PDick G(2010)Implicitly controlling bloat in genetic programmingIEEE Transactions on Evolutionary Computation10.1109/TEVC.2009.202731414:2(173-190)Online publication date: 1-Apr-2010
https://dl.acm.org/doi/10.1109/TEVC.2009.2027314
Seo KHyun SGoodman ERothlauf F(2009)Tree-structure-aware GP operators for automatic gait generation of quadruped robotProceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers10.1145/1570256.1570293(2155-2160)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1570256.1570293
Silva SCosta E(2009)Dynamic limits for bloat control in genetic programming and a review of past and current bloat theoriesGenetic Programming and Evolvable Machines10.1007/s10710-008-9075-910:2(141-179)Online publication date: 1-Jun-2009
https://dl.acm.org/doi/10.1007/s10710-008-9075-9
William ENorthern J(2008)Genetic Programming Lab (GPLab) Tool Set Version 3.02008 IEEE Region 5 Conference10.1109/TPSD.2008.4562729(1-6)Online publication date: Apr-2008
https://doi.org/10.1109/TPSD.2008.4562729
Tuze Kuyucu Trefzer MGreensted AMiller JTyrrell A(2008)Fitness functions for the unconstrained evolution of digital circuits2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)10.1109/CEC.2008.4631145(2584-2591)Online publication date: Jun-2008
https://doi.org/10.1109/CEC.2008.4631145
Kouchakpour PZaknich ABräunl T(2008)A survey and taxonomy of performance improvement of canonical genetic programmingKnowledge and Information Systems10.1007/s10115-008-0184-921:1(1-39)Online publication date: 12-Dec-2008
https://doi.org/10.1007/s10115-008-0184-9
Clifton MFang G(2007)Genetic Programming in Robot Exploration2007 International Conference on Mechatronics and Automation10.1109/ICMA.2007.4303585(451-456)Online publication date: Aug-2007
https://doi.org/10.1109/ICMA.2007.4303585
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