### Abstract

In many practical problems-from tracking aircraft based on radar data to building a bibliographic database based on citation lists-we want to reason about an unbounded number of unseen objects with unknown relations among them. Bayesian networks, which define a fixed dependency structure on a finite set of variables, are not the ideal representation language for this task. This paper introduces contingent Bayesian networks (CBNs), which represent uncertainty about dependencies by labeling each edge with a condition under which it is active. A CBN may contain cycles and have infinitely many variables. Nevertheless, we give general conditions under which such a CBN defines a unique joint distribution over its variables. We also present a likelihood weighting algorithm that performs approximate inference in finite time per sampling step on any CBN that satisfies these conditions.

Original language | English (US) |
---|---|

Title of host publication | AISTATS 2005 - Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics |

Pages | 238-245 |

Number of pages | 8 |

State | Published - Dec 1 2005 |

Event | 10th International Workshop on Artificial Intelligence and Statistics, AISTATS 2005 - Hastings, Christ Church, Barbados Duration: Jan 6 2005 → Jan 8 2005 |

### Publication series

Name | AISTATS 2005 - Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics |
---|

### Other

Other | 10th International Workshop on Artificial Intelligence and Statistics, AISTATS 2005 |
---|---|

Country | Barbados |

City | Hastings, Christ Church |

Period | 1/6/05 → 1/8/05 |

### ASJC Scopus subject areas

- Artificial Intelligence
- Statistics and Probability

## Fingerprint Dive into the research topics of 'Approximate inference for infinite contingent Bayesian networks'. Together they form a unique fingerprint.

## Cite this

*AISTATS 2005 - Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics*(pp. 238-245). (AISTATS 2005 - Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics).