| Texto completo | |
| Autor(es): |
Cozman, Fabio Gagliardi
;
Maua, Denis Deratani
Número total de Autores: 2
|
| Tipo de documento: | Artigo Científico |
| Fonte: | INTERNATIONAL JOURNAL OF APPROXIMATE REASONING; v. 125, p. 22-pg., 2020-10-01. |
| Resumo | |
Probabilistic Answer Set Programming (PASP) combines rules, facts, and independent probabilistic facts. We argue that a very useful modeling paradigm is obtained by adopting a particular semantics for PASP, where one associates a credal set with each consistent program. We examine the basic properties of PASP under this credal semantics, in particular presenting novel results on its complexity and its expressivity, and we introduce an inference algorithm to compute (upper) probabilities given a program. (C) 2020 Elsevier Inc. All rights reserved. (AU) | |
| Processo FAPESP: | 19/07665-4 - Centro de Inteligência Artificial |
| Beneficiário: | Fabio Gagliardi Cozman |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa eScience e Data Science - Centros de Pesquisa Aplicada |
| Processo FAPESP: | 16/18841-0 - Algoritmos para inferência e aprendizado de programas lógicos probabilísticos |
| Beneficiário: | Fabio Gagliardi Cozman |
| Modalidade de apoio: | Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE |