The Inferential Complexity of Bayesian and Credal Networks
Abstract
This paper presents new results on the complexity of graph-theoretical models that represent probabilities (Bayesian networks) and that represent interval and set valued probabilities (credal networks). We define a new class of networks with bounded width, and introduce a new decision problem for Bayesian networks, the maximin a posteriori. We present new links between the Bayesian and credal networks, and present new results both for Bayesian networks (most probable explanation with observations, maximin a posteriori) and for credal networks (bounds on probabilities a posteriori, most probable explanation with and without observations, maximum a posteriori). 1
Cite
Text
de Campos and Cozman. "The Inferential Complexity of Bayesian and Credal Networks." International Joint Conference on Artificial Intelligence, 2005.Markdown
[de Campos and Cozman. "The Inferential Complexity of Bayesian and Credal Networks." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/decampos2005ijcai-inferential/)BibTeX
@inproceedings{decampos2005ijcai-inferential,
title = {{The Inferential Complexity of Bayesian and Credal Networks}},
author = {de Campos, Cassio Polpo and Cozman, Fábio Gagliardi},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2005},
pages = {1313-1318},
url = {https://mlanthology.org/ijcai/2005/decampos2005ijcai-inferential/}
}