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Explaining SOMA: The relation of stochastic perturbation to population diversity and parameter space coverage

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F21%3A63544458" target="_blank" >RIV/70883521:28140/21:63544458 - isvavai.cz</a>

  • Result on the web

    <a href="https://dl.acm.org/doi/pdf/10.1145/3449726.3463211" target="_blank" >https://dl.acm.org/doi/pdf/10.1145/3449726.3463211</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3449726.3463211" target="_blank" >10.1145/3449726.3463211</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Explaining SOMA: The relation of stochastic perturbation to population diversity and parameter space coverage

  • Original language description

    The Self-Organizing Migrating Algorithm (SOMA) is enjoying a renewed interest of the research community, following recent achievements in various application areas and renowned performance competitions. In this paper, we focus on the importance and effect of the perturbation operator in SOMA as the perturbation is one of the fundamental inner principles of SOMA. In this in-depth study, we present data, visualizations, and analysis of the effect of the perturbation on the population, its diversity and average movement patterns. We provide evidence that there is a direct relation between the perturbation intensity (set by control parameter prt) and the rate of diversity loss. The perturbation setting further affects the exploratory ability of the algorithm, as is demonstrated here by analysing the parameter space coverage of the population. We aim to provide insight and explanation of the impact of perturbation in SOMA for future researchers and practitioners. © 2021 ACM.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion

  • ISBN

    978-145038351-6

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    1944-1952

  • Publisher name

    Association for Computing Machinery

  • Place of publication

    New York

  • Event location

    Lille

  • Event date

    Jul 10, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article