| Texto completo | |
| Autor(es): |
Revoredo, Kate
;
Ochoa-Luna, Jose Eduardo
;
Cozman, Fabio Gagliardi
;
Costa, ACD
;
Vicari, RM
;
Tonidandel, F
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | ADVANCES IN ARTIFICIAL INTELLIGENCE - SBIA 2010; v. 6404, p. 10-pg., 2010-01-01. |
| Resumo | |
This paper investigates learning methods where the target language is the recently proposed probabilistic description logic CR ALC. We start with an inductive logic programming algorithm that learns logical constructs; we then develop an algorithm that learns probabilistic constructs by searching for conditioning concepts, using examples given as interpretations. Issues on learning from entailments are also examined, and practical examples are discussed. (AU) | |
| Processo FAPESP: | 08/03995-5 - LOGPROB: lógica probabilística - fundamentos e aplicações computacionais |
| Beneficiário: | Marcelo Finger |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |