A framework for the analysis and synthesis of Swarm Intelligence algorithms

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dc.creatorDávila Patrícia Ferreira Cruz
dc.creatorRenato Dourado Maia
dc.creatorLeandro Nunes de Castro
dc.date.accessioned2022-07-06T13:28:40Z
dc.date.accessioned2025-09-08T23:24:32Z
dc.date.available2022-07-06T13:28:40Z
dc.date.issued2020-03-28
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.description.sponsorshipFAPESP - Fundação de Amparo à Pesquisa do Estado de São Paulo
dc.description.sponsorshipOutra Agência
dc.identifier.doihttps://doi.org/10.1080/0952813X.2020.1764635
dc.identifier.issn0952-813X
dc.identifier.urihttps://hdl.handle.net/1843/42961
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofJournal of Experimental and Theoretical Artificial Intelligence
dc.rightsAcesso Restrito
dc.subjectFramework (Arquivo de computador)
dc.subjectAlgoritmos computacionais
dc.subjectInteligência coletiva
dc.titleA framework for the analysis and synthesis of Swarm Intelligence algorithms
dc.typeArtigo de periódico
local.citation.epage23
local.citation.spage1
local.citation.volume33
local.description.resumoOver the last decades, the number of Swarm Intelligence algorithms proposed in the literature has increased considerably. However, most algorithms do not follow an adequate scientific rigour neither the principles of Swarm Intelligence, reproducing similar computational procedures of many other approaches, but by means of a different metaphor. In this scenario, the aim of this paper is to propose a framework for the analysis and synthesis of Swarm Intelligence algorithms that can contribute to a structured understanding (analysis) and development (synthesis) of these algorithms. The main objective of the proposed framework is to guide the construction of Swarm Intelligence metaphors in a consistent and well-founded way, as well as to contribute with the analysis and development of new algorithms that had better encompass the features and abilities of insects’ societies.
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://www.tandfonline.com/doi/abs/10.1080/0952813X.2020.1764635

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