Fast local search methods for solving limited memory influence diagrams (2016)
- Authors:
- USP affiliated authors: MAUÁ, DENIS DERATANI - IME ; COZMAN, FABIO GAGLIARDI - EP
- Unidades: IME; EP
- DOI: 10.1016/j.ijar.2015.05.003
- Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS; INTELIGÊNCIA ARTIFICIAL; PROBABILIDADE APLICADA
- Language: Inglês
- Imprenta:
- Source:
- Título: International Journal of Approximate Reasoning
- ISSN: 1873-4731
- Volume/Número/Paginação/Ano: v. 68, p. 230-245, Jan. 2016
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
MAUÁ, Denis Deratani e COZMAN, Fabio Gagliardi. Fast local search methods for solving limited memory influence diagrams. International Journal of Approximate Reasoning, v. 68, n. Ja 2016, p. 230-245, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2015.05.003. Acesso em: 12 fev. 2026. -
APA
Mauá, D. D., & Cozman, F. G. (2016). Fast local search methods for solving limited memory influence diagrams. International Journal of Approximate Reasoning, 68( Ja 2016), 230-245. doi:10.1016/j.ijar.2015.05.003 -
NLM
Mauá DD, Cozman FG. Fast local search methods for solving limited memory influence diagrams [Internet]. International Journal of Approximate Reasoning. 2016 ; 68( Ja 2016): 230-245.[citado 2026 fev. 12 ] Available from: https://doi.org/10.1016/j.ijar.2015.05.003 -
Vancouver
Mauá DD, Cozman FG. Fast local search methods for solving limited memory influence diagrams [Internet]. International Journal of Approximate Reasoning. 2016 ; 68( Ja 2016): 230-245.[citado 2026 fev. 12 ] Available from: https://doi.org/10.1016/j.ijar.2015.05.003 - Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks
- Probabilistic logic programming under the L-Stable semantics
- Specifying credal sets with probabilistic answer set programming
- The complexity of inferences and explanations in probabilistic logic programming
- The descriptive complexity of bayesian network specifications
- Robustifying sum-product networks
- The complexity of Bayesian networks specified by propositional and relational languages
- The finite model theory of bayesian networks: descriptive complexity
- Bayesian networks specified using propositional and relational constructs: combined, data, and domain complexity
- The complexity of MAP inference in Bayesian networks specified through logical languages
Informações sobre o DOI: 10.1016/j.ijar.2015.05.003 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| Cozman-2016-Fast local se... |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
