Progressive Insular Cooperative GP

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Abstract

This work presents a novel genetic programming system for multi-class classification, called progressively insular cooperative genetic programming (PIC GP). Based on the idea that effective multiclass classification can be obtained by appropriately joining classifiers that are highly specialized on the single classes, PIC GP evolves, at the same time, two populations. The first population contains individuals called specialists, and each specialist is optimized on one specific target class. The second population contains higher-level individuals, called teams, that join specialists to obtain the final algorithm prediction. By means of three simple parameters, PIC GP can tune the amount of cooperation between specialists of different classes. The first part of the paper is dedicated to a study of the influence of these parameters on the evolution dynamics. The obtained results indicate that PIC GP achieves the best performance when the evolution begins with a high level of cooperation between specialists of different classes, and then this type of cooperation is progressively decreased, until only specialists of the same class can cooperate between each other. The last part of the work is dedicated to an experimental comparison between PIC GP and a set of state-of-the-art classification algorithms. The presented results indicate that PIC GP outperforms the majority of its competitors on the studied test problems.

Original languageEnglish
Title of host publicationGenetic Programming
Subtitle of host publication24th European Conference, EuroGP 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings
EditorsTing Hu, Nuno Lourenço, Eric Medvet
PublisherSpringer Science and Business Media Deutschland GmbH
Pages19-35
Number of pages17
ISBN (Print)9783030728113
DOIs
Publication statusPublished - 25 Mar 2021
Event24th European Conference on Genetic Programming, EuroGP 2021 - Virtual, Online
Duration: 7 Apr 20219 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12691 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th European Conference on Genetic Programming, EuroGP 2021
CityVirtual, Online
Period7/04/219/04/21

Keywords

  • Cooperative evolution
  • Genetic programming
  • Multiclass classification

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