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Progressive Insular Cooperative GP

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Book cover Genetic Programming (EuroGP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12691))

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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.

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Acknowledgments

This work was partially supported by FCT, Portugal, through funding of projects BINDER (PTDC/CCI-INF/29168/2017) and AICE (DSAIPA/DS/0113/2019).

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Authors and Affiliations

  1. NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisbon, Portugal

    Karina Brotto Rebuli & Leonardo Vanneschi

  2. Dipartimento di Scienze Veterinarie, Università degli Studi di Torino, Largo Paolo Braccini 2, 10095, Turin, Italy

    Karina Brotto Rebuli

Authors
  1. Karina Brotto Rebuli
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  2. Leonardo Vanneschi
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Corresponding authors

Correspondence to Karina Brotto Rebuli or Leonardo Vanneschi .

Editor information

Editors and Affiliations

  1. Queen’s University, Kingston, ON, Canada

    Ting Hu

  2. University of Coimbra, Coimbra, Portugal

    Nuno Lourenço

  3. University of Trieste, Trieste, Italy

    Eric Medvet

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Brotto Rebuli, K., Vanneschi, L. (2021). Progressive Insular Cooperative GP. In: Hu, T., Lourenço, N., Medvet, E. (eds) Genetic Programming. EuroGP 2021. Lecture Notes in Computer Science(), vol 12691. Springer, Cham. https://doi.org/10.1007/978-3-030-72812-0_2

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  • DOI: https://doi.org/10.1007/978-3-030-72812-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72811-3

  • Online ISBN: 978-3-030-72812-0

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