Probabilistic logic with strong independence
| dc.contributor.author | Cozman F.G. | |
| dc.contributor.author | De Campos C.P. | |
| dc.contributor.author | Da Rocha J.C.F. | |
| dc.date.accessioned | 2024-03-13T01:43:05Z | |
| dc.date.available | 2024-03-13T01:43:05Z | |
| dc.date.issued | 2006 | |
| dc.description.abstract | This papers investigates the manipulation of statements of strong independence in probabilistic logic. Inference methods based on polynomial programming are presented for strong independence, both for unconditional and conditional cases. We also consider graph-theoretic representations, where each node in a graph is associated with a Boolean variable and edges carry a Markov condition. The resulting model generalizes Bayesian networks, allowing probabilistic assessments and logical constraints to be mixed. © Springer-Verlag Berlin Heidelberg 2006. | |
| dc.description.firstpage | 612 | |
| dc.description.lastpage | 621 | |
| dc.description.volume | 4140 LNAI | |
| dc.identifier.doi | 10.1007/11874850_65 | |
| dc.identifier.issn | 1611-3349 | |
| dc.identifier.uri | https://dspace.mackenzie.br/handle/10899/37822 | |
| dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
| dc.rights | Acesso Restrito | |
| dc.title | Probabilistic logic with strong independence | |
| dc.type | Artigo de evento | |
| local.scopus.citations | 0 | |
| local.scopus.eid | 2-s2.0-33751371479 | |
| local.scopus.subject | Bayesian networks | |
| local.scopus.subject | Conditional cases | |
| local.scopus.subject | Polynomial programming | |
| local.scopus.updated | 2024-05-01 | |
| local.scopus.url | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33751371479&origin=inward |