### Resumen

© Springer-Verlag Berlin Heidelberg 2002. Probabilistic models and graph-based independence languages have often been combined in artificial intelligence research. The Bayesian network formalism is probably the best example of this type of association. In this article we focus on graphical structures that associate graphs with sets of probability measures — the result is referred to as a credal network. We describe credal networks and review an algorithm for evidential reasoning that we have recently developed. The algorithm substantially simplifies the computation of upper and lower probabilities by exploiting an independence assumption (strong independence) and a representation based on separately specified sets of probability measures. The algorithm is particularly efficient when applied to polytree structures. We then discuss a strategy for approximate reasoning in multi-connected networks, based on conditioning.

Idioma original | Inglés estadounidense |
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Título de la publicación alojada | Evidence propagation in credal networks: An exact algorithm based on separately specified sets of probability |

Páginas | 376-385 |

Número de páginas | 10 |

ISBN (versión digital) | 3540001247, 9783540001249 |

DOI | |

Estado | Publicada - 1 ene 2002 |

Publicado de forma externa | Sí |

Evento | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - Duración: 1 ene 2018 → … |

### Serie de la publicación

Nombre | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volumen | 2507 |

ISSN (versión impresa) | 0302-9743 |

### Conferencia

Conferencia | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Período | 1/01/18 → … |

## Huella Profundice en los temas de investigación de 'Evidence propagation in credal networks: An exact algorithm based on separately specified sets of probability'. En conjunto forman una huella única.

## Citar esto

da Rocha, J. C. F., & Cozman, F. G. (2002). Evidence propagation in credal networks: An exact algorithm based on separately specified sets of probability. En

*Evidence propagation in credal networks: An exact algorithm based on separately specified sets of probability*(pp. 376-385). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2507). https://doi.org/10.1007/3-540-36127-8_36