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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/42964
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dc.creatorDávila Patrícia Ferreira Cruzpt_BR
dc.creatorRenato Dourado Maiapt_BR
dc.creatorLeandro Nunes de Castropt_BR
dc.date.accessioned2022-07-06T14:03:06Z-
dc.date.available2022-07-06T14:03:06Z-
dc.date.issued2019-03-04-
dc.citation.volume12pt_BR
dc.citation.spage189pt_BR
dc.citation.epage200pt_BR
dc.identifier.doihttps://doi.org/10.1007/s12065-019-00209-pt_BR
dc.identifier.issn1864-5917pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/42964-
dc.description.resumoThe literature is now filled with swarm intelligence algorithms developed by taking inspiration from a number of insects and other animals and phenomena, such as ants, termites, bees, fishes and cockroaches, to name just a few. Many, if not most, of these bioinspirations carry with them some common issues and features which happen at the individual level, promoting very similar collective emergent phenomena. Thus, despite using different biological metaphors as inspiration, most algorithms present a similar structure and it is possible to identify common macro-processes among them. In this context, this paper identifies a set of common features among some well-known swarm-based algorithms and how each of these approaches implement them. By doing this, we provide the community with the core features of swarm-intelligence algorithms. This diagnostic is crucial and timely to the field, because once we are able to list and explain these commonalities, we are also able to better analyze and design swarm intelligence algorithms.pt_BR
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológicopt_BR
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.description.sponsorshipFAPESP - Fundação de Amparo à Pesquisa do Estado de São Paulopt_BR
dc.description.sponsorshipOutra Agênciapt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIASpt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofEvolutionary Intelligencept_BR
dc.rightsAcesso Abertopt_BR
dc.subject.otherAlgoritmospt_BR
dc.subject.otherInteligência coletivapt_BR
dc.titleA critical discussion into the core of swarm intelligence algorithmspt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://link.springer.com/article/10.1007/s12065-019-00209-6pt_BR
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