Complexity results for probabilistic answer set programming (2020)
- Authors:
- USP affiliated authors: MAUÁ, DENIS DERATANI - IME ; COZMAN, FABIO GAGLIARDI - EP
- Unidades: IME; EP
- DOI: 10.1016/j.ijar.2019.12.003
- Assunto: COMPUTABILIDADE E COMPLEXIDADE
- Keywords: Probabilistic logic programming; Answer set programming; Computational complexity
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: International Journal of Approximate Reasoning
- ISSN: 0888-613X
- Volume/Número/Paginação/Ano: v.118, p. 133-154, 2020
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
MAUÁ, Denis Deratani e COZMAN, Fabio Gagliardi. Complexity results for probabilistic answer set programming. International Journal of Approximate Reasoning, v. 118, p. 133-154, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2019.12.003. Acesso em: 09 fev. 2026. -
APA
Mauá, D. D., & Cozman, F. G. (2020). Complexity results for probabilistic answer set programming. International Journal of Approximate Reasoning, 118, 133-154. doi:10.1016/j.ijar.2019.12.003 -
NLM
Mauá DD, Cozman FG. Complexity results for probabilistic answer set programming [Internet]. International Journal of Approximate Reasoning. 2020 ;118 133-154.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1016/j.ijar.2019.12.003 -
Vancouver
Mauá DD, Cozman FG. Complexity results for probabilistic answer set programming [Internet]. International Journal of Approximate Reasoning. 2020 ;118 133-154.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1016/j.ijar.2019.12.003 - Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks
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- Thirty years of credal networks: specification, algorithms and complexity
- Probabilistic logic programming under the L-Stable semantics
- The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws
- 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
Informações sobre o DOI: 10.1016/j.ijar.2019.12.003 (Fonte: oaDOI API)
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