The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws (2019)
- Authors:
- USP affiliated authors: COZMAN, FABIO GAGLIARDI - EP ; MAUÁ, DENIS DERATANI - IME
- Unidades: EP; IME
- DOI: 10.1016/j.ijar.2019.04.003
- Subjects: TEORIA DA COMPUTAÇÃO; TEORIA DOS MODELOS; AQUISIÇÃO DE CONHECIMENTO; LÓGICA MATEMÁTICA
- Keywords: Bayesian networks; Finite model theory; Probabilistic relational models; Descriptive complexity; Zero/one laws; Probabilistic logic
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: International Journal of Approximate Reasoning
- ISSN: 0888-613X
- Volume/Número/Paginação/Ano: v. 110, p. 107-126, 2019
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
- Licença: publisher-specific-oa
-
ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws. International Journal of Approximate Reasoning, v. 110, p. 107-126, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2019.04.003. Acesso em: 27 dez. 2025. -
APA
Cozman, F. G., & Mauá, D. D. (2019). The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws. International Journal of Approximate Reasoning, 110, 107-126. doi:10.1016/j.ijar.2019.04.003 -
NLM
Cozman FG, Mauá DD. The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws [Internet]. International Journal of Approximate Reasoning. 2019 ; 110 107-126.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1016/j.ijar.2019.04.003 -
Vancouver
Cozman FG, Mauá DD. The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws [Internet]. International Journal of Approximate Reasoning. 2019 ; 110 107-126.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1016/j.ijar.2019.04.003 - Fast local search methods for solving limited memory influence diagrams
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Informações sobre o DOI: 10.1016/j.ijar.2019.04.003 (Fonte: oaDOI API)
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