All the Truth About NEvAr

Detalhes bibliográficos
Autor(a) principal: Machado, Penousal
Data de Publicação: 2002
Outros Autores: Cardoso, Amílcar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/7641
https://doi.org/10.1023/A:1013662402341
Resumo: The use of Evolutionary Computation approaches to generate images has reached a great popularity. This led to the emergence of a new art form—Evolutionary Art—and to the proliferation of Evolutionary Art Tools. In this paper, we present an Evolutionary Art Tool, NEvAr, the experimental results achieved, and the work methodology used to generate images. In NEvAr, useful individuals are stored in a database in order to allow their reuse. This database is playing an increasingly important role in the creation of new images, which led us to the development of automatic seeding procedures, also described. The automation of fitness assignment is one of our present research interests. We will, therefore, describe some preliminary results achieved with our current approach to automatic evaluation.
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spelling All the Truth About NEvArThe use of Evolutionary Computation approaches to generate images has reached a great popularity. This led to the emergence of a new art form—Evolutionary Art—and to the proliferation of Evolutionary Art Tools. In this paper, we present an Evolutionary Art Tool, NEvAr, the experimental results achieved, and the work methodology used to generate images. In NEvAr, useful individuals are stored in a database in order to allow their reuse. This database is playing an increasingly important role in the creation of new images, which led us to the development of automatic seeding procedures, also described. The automation of fitness assignment is one of our present research interests. We will, therefore, describe some preliminary results achieved with our current approach to automatic evaluation.2002info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/7641http://hdl.handle.net/10316/7641https://doi.org/10.1023/A:1013662402341engApplied Intelligence. 16:2 (2002) 101-118Machado, PenousalCardoso, Amílcarinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2021-09-22T10:33:04Zoai:estudogeral.uc.pt:10316/7641Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:58:18.466542Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv All the Truth About NEvAr
title All the Truth About NEvAr
spellingShingle All the Truth About NEvAr
Machado, Penousal
title_short All the Truth About NEvAr
title_full All the Truth About NEvAr
title_fullStr All the Truth About NEvAr
title_full_unstemmed All the Truth About NEvAr
title_sort All the Truth About NEvAr
author Machado, Penousal
author_facet Machado, Penousal
Cardoso, Amílcar
author_role author
author2 Cardoso, Amílcar
author2_role author
dc.contributor.author.fl_str_mv Machado, Penousal
Cardoso, Amílcar
description The use of Evolutionary Computation approaches to generate images has reached a great popularity. This led to the emergence of a new art form—Evolutionary Art—and to the proliferation of Evolutionary Art Tools. In this paper, we present an Evolutionary Art Tool, NEvAr, the experimental results achieved, and the work methodology used to generate images. In NEvAr, useful individuals are stored in a database in order to allow their reuse. This database is playing an increasingly important role in the creation of new images, which led us to the development of automatic seeding procedures, also described. The automation of fitness assignment is one of our present research interests. We will, therefore, describe some preliminary results achieved with our current approach to automatic evaluation.
publishDate 2002
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https://doi.org/10.1023/A:1013662402341
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dc.relation.none.fl_str_mv Applied Intelligence. 16:2 (2002) 101-118
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