Resumen
© Copyright 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. We examine the inferential complexity of Bayesian networks specified through logical constructs. We first consider simple propositional languages, and then move to relational languages. We examine both the combined complexity of inference (as network size and evidence size are not bounded) and the data complexity of inference (where network size is bounded); we also examine the connection to liftability through domain complexity. Combined and data complexity of several inference problems are presented, ranging from polynomial to exponential classes.
| Idioma original | Inglés estadounidense |
|---|---|
| Páginas | 3519-3525 |
| Número de páginas | 7 |
| Estado | Publicada - 1 jun 2015 |
| Publicado de forma externa | Sí |
| Evento | Proceedings of the National Conference on Artificial Intelligence - Duración: 1 jun 2015 → … |
Conferencia
| Conferencia | Proceedings of the National Conference on Artificial Intelligence |
|---|---|
| Período | 1/06/15 → … |
Huella Profundice en los temas de investigación de 'Bayesian networks specified using propositional and relational constructs: Combined, data, and domain complexity'. En conjunto forman una huella única.
Citar esto
Cozman, F. G., & Mauá, D. D. (2015). Bayesian networks specified using propositional and relational constructs: Combined, data, and domain complexity. 3519-3525. Papel presentado en Proceedings of the National Conference on Artificial Intelligence, .