The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference (2020)
- Authors:
- USP affiliated authors: COZMAN, FABIO GAGLIARDI - EP ; MAUÁ, DENIS DERATANI - IME
- Unidades: EP; IME
- DOI: 10.1016/j.ijar.2020.07.004
- Subjects: PROGRAMAÇÃO LÓGICA; COMPUTABILIDADE E COMPLEXIDADE
- Keywords: Logic programming; Answer Set Programming; Probabilistic programming; Credal sets; Computational complexity; Descriptive complexity
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: International Journal of Approximate Reasoning
- ISSN: 0888-613X
- Volume/Número/Paginação/Ano: v. 125, p. 218-239, 2020
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, v. 125, p. 218-239, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2020.07.004. Acesso em: 09 fev. 2026. -
APA
Cozman, F. G., & Mauá, D. D. (2020). The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, 125, 218-239. doi:10.1016/j.ijar.2020.07.004 -
NLM
Cozman FG, Mauá DD. The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference [Internet]. International Journal of Approximate Reasoning. 2020 ; 125 218-239.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1016/j.ijar.2020.07.004 -
Vancouver
Cozman FG, Mauá DD. The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference [Internet]. International Journal of Approximate Reasoning. 2020 ; 125 218-239.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1016/j.ijar.2020.07.004 - Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks
- Thirty years of credal networks: specification, algorithms and complexity
- 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
- Complexity results for probabilistic answer set programming
Informações sobre o DOI: 10.1016/j.ijar.2020.07.004 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3003176.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
