A generative power-law search tree model

Detalhes bibliográficos
Autor(a) principal: Carvalho, Alda
Data de Publicação: 2009
Outros Autores: Crato, Nuno, Gomes, Carla
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/27674
Resumo: It is now a well-established fact that search algorithms can exhibit heavy-tailed behavior. However, the reasons behind this fact are not well understood. We provide a generative search tree model whose distribution of the number of nodes visited during search is formally heavy-tailed. Our model allows us to generate search trees with any degree of heavy-tailedness. We also show how the different regimes observed for the runtime distributions of backtrack search methods across different constrainedness regions of random CSP models can be captured by a mixture of the so-called stable distributions.
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spelling A generative power-law search tree modelRandom AlgorithmsHeavy-tailsComputational StatisticsIt is now a well-established fact that search algorithms can exhibit heavy-tailed behavior. However, the reasons behind this fact are not well understood. We provide a generative search tree model whose distribution of the number of nodes visited during search is formally heavy-tailed. Our model allows us to generate search trees with any degree of heavy-tailedness. We also show how the different regimes observed for the runtime distributions of backtrack search methods across different constrainedness regions of random CSP models can be captured by a mixture of the so-called stable distributions.ElsevierRepositório da Universidade de LisboaCarvalho, AldaCrato, NunoGomes, Carla2023-04-28T13:58:25Z20092009-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/27674engCarvalho, Alda; Nuno Crato and Carla Gomes .(2009). “A generative power-law search tree model”. Computers & Operations Research, Vol. 36: pp. 2376 – 2386. (Search PDF in 2023).0305-054810.1016/j.cor.2008.08.017info: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:RCAAP2023-04-30T01:30:56Zoai:www.repository.utl.pt:10400.5/27674Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:50:29.060428Repositório 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 A generative power-law search tree model
title A generative power-law search tree model
spellingShingle A generative power-law search tree model
Carvalho, Alda
Random Algorithms
Heavy-tails
Computational Statistics
title_short A generative power-law search tree model
title_full A generative power-law search tree model
title_fullStr A generative power-law search tree model
title_full_unstemmed A generative power-law search tree model
title_sort A generative power-law search tree model
author Carvalho, Alda
author_facet Carvalho, Alda
Crato, Nuno
Gomes, Carla
author_role author
author2 Crato, Nuno
Gomes, Carla
author2_role author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Carvalho, Alda
Crato, Nuno
Gomes, Carla
dc.subject.por.fl_str_mv Random Algorithms
Heavy-tails
Computational Statistics
topic Random Algorithms
Heavy-tails
Computational Statistics
description It is now a well-established fact that search algorithms can exhibit heavy-tailed behavior. However, the reasons behind this fact are not well understood. We provide a generative search tree model whose distribution of the number of nodes visited during search is formally heavy-tailed. Our model allows us to generate search trees with any degree of heavy-tailedness. We also show how the different regimes observed for the runtime distributions of backtrack search methods across different constrainedness regions of random CSP models can be captured by a mixture of the so-called stable distributions.
publishDate 2009
dc.date.none.fl_str_mv 2009
2009-01-01T00:00:00Z
2023-04-28T13:58:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/27674
url http://hdl.handle.net/10400.5/27674
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Carvalho, Alda; Nuno Crato and Carla Gomes .(2009). “A generative power-law search tree model”. Computers & Operations Research, Vol. 36: pp. 2376 – 2386. (Search PDF in 2023).
0305-0548
10.1016/j.cor.2008.08.017
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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