research-article

Enhanced generalized ant programming (EGAP)

Authors:

Amirali Salehi-Abari,

Tony WhiteAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 111 - 118

https://doi.org/10.1145/1389095.1389111

Published: 12 July 2008 Publication History

Abstract

This paper begins by reviewing different methods of automatic programming while emphasizing the technique of Ant Programming (AP). AP uses an ant foraging metaphor in which ants generate a program by moving through a graph. Generalized Ant Programming (GAP) uses a context-free grammar and an Ant Colony System (ACS) to guide the program generation search process. There are two enhancements to GAP that are proposed in this paper. These are: providing a heuristic for path termination inspired by building construction and a novel pheromone placement algorithm. Three well-known problems -- Quartic symbolic regression, multiplexer, and an ant trail problem -- are experimentally compared using enhanced GAP (EGAP) and GAP. The results of the experiments show the statistically significant advantage of using this heuristic function and pheromone placement algorithm of EGAP over GAP.

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Cited By

Rueda RRuiz LCuéllar MPegalajar M(2020)An Ant Colony Optimization approach for symbolic regression using Straight Line Programs. Application to energy consumption modellingInternational Journal of Approximate Reasoning10.1016/j.ijar.2020.03.005Online publication date: Mar-2020
https://doi.org/10.1016/j.ijar.2020.03.005
Mahanipour ANezamabadi-Pour H(2019)GSPApplied Intelligence10.1007/s10489-018-1327-749:4(1502-1516)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s10489-018-1327-7
Kim KShan YNguyen XMckay R(2014)Probabilistic model building in genetic programmingGenetic Programming and Evolvable Machines10.1007/s10710-013-9205-x15:2(115-167)Online publication date: 1-Jun-2014
https://dl.acm.org/doi/10.1007/s10710-013-9205-x
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Index Terms

Enhanced generalized ant programming (EGAP)
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Intelligent agents

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

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Published: 12 July 2008

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GECCO08

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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

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Cited By

Rueda RRuiz LCuéllar MPegalajar M(2020)An Ant Colony Optimization approach for symbolic regression using Straight Line Programs. Application to energy consumption modellingInternational Journal of Approximate Reasoning10.1016/j.ijar.2020.03.005Online publication date: Mar-2020
https://doi.org/10.1016/j.ijar.2020.03.005
Mahanipour ANezamabadi-Pour H(2019)GSPApplied Intelligence10.1007/s10489-018-1327-749:4(1502-1516)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s10489-018-1327-7
Kim KShan YNguyen XMckay R(2014)Probabilistic model building in genetic programmingGenetic Programming and Evolvable Machines10.1007/s10710-013-9205-x15:2(115-167)Online publication date: 1-Jun-2014
https://dl.acm.org/doi/10.1007/s10710-013-9205-x
Pappa GOchoa GHyde MFreitas AWoodward JSwan J(2014)Contrasting meta-learning and hyper-heuristic researchGenetic Programming and Evolvable Machines10.1007/s10710-013-9186-915:1(3-35)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1007/s10710-013-9186-9
Olmo JRomero JVentura S(2014)Swarm-based metaheuristics in automatic programmingWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery10.1002/widm.11384:6(445-469)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1002/widm.1138
Olmo JLuna JRomero JVentura S(2013)Mining association rules with single and multi-objective grammar guided ant programmingIntegrated Computer-Aided Engineering10.3233/ICA-13043020:3(217-234)Online publication date: 1-Jul-2013
https://dl.acm.org/doi/10.3233/ICA-130430
Hara AKushida JTanabe STakahama T(2013)Parallel Ant Programming using genetic operators2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)10.1109/IWCIA.2013.6624788(75-80)Online publication date: Jul-2013
https://doi.org/10.1109/IWCIA.2013.6624788
Olmo JRomero JVentura S(2012)Classification rule mining using ant programming guided by grammar with multiple Pareto frontsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-012-0883-816:12(2143-2163)Online publication date: 1-Dec-2012
https://dl.acm.org/doi/10.1007/s00500-012-0883-8
Olmo JRomero JVentura S(2011)Using Ant Programming Guided by Grammar for Building Rule-Based ClassifiersIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics10.1109/TSMCB.2011.215768141:6(1585-1599)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1109/TSMCB.2011.2157681
Olmo JRomero JVentura S(2010)A grammar based Ant Programming algorithm for mining classification rulesIEEE Congress on Evolutionary Computation10.1109/CEC.2010.5586492(1-8)Online publication date: Jul-2010
https://doi.org/10.1109/CEC.2010.5586492

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