### Resumen

© Springer-Verlag Berlin Heidelberg 1999. This paper investigates Walley’s concepts of irrelevance and independence, as applied to the theory of closed convex sets of probability measures. Walley’s concepts are analyzed from the perspective of axioms for conditional independence (the so-called semi-graphoid axioms). Two new results are demonstrated in discrete models: rst, Walley’s concept of irrelevance is an asymmetric semi-graphoid; second, Walley’s concept of independence is an incomplete semi-graphoid. These results are the basis for an understanding of irrelevance and independence in connection to the theory of closed convex sets of probability measures, a theory that has received attention as a powerful representation for uncertainty in beliefs and preferences.

Idioma original | Inglés estadounidense |
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Título de la publicación alojada | Irrelevance and independence axioms in Quasi-Bayesian theory |

Páginas | 128-136 |

Número de páginas | 9 |

ISBN (versión digital) | 354066131X, 9783540661313 |

Estado | Publicada - 1 ene 1999 |

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 | 1638 |

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 'Irrelevance and independence axioms in Quasi-Bayesian theory'. En conjunto forman una huella única.

## Citar esto

Cozman, F. G. (1999). Irrelevance and independence axioms in Quasi-Bayesian theory. En

*Irrelevance and independence axioms in Quasi-Bayesian theory*(pp. 128-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1638).