The Inferential Complexity of Bayesian and Credal Networks
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1313-1317.
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).
@inproceedings{ijcai2005p92,
title = {The Inferential Complexity of Bayesian and Credal Networks},
author = {de Campos, Cassio Polpo and Cozman, Fabio Gagliardi},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {1313--1317},
year = {2005},
url = {https://ijcai.org/proceedings/2005/92},
}
TY - CPAPER TI - The Inferential Complexity of Bayesian and Credal Networks AU - de Campos, Cassio Polpo AU - Cozman, Fabio Gagliardi T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 1313 EP - 1317 UR - https://ijcai.org/proceedings/2005/92 ER -Copied
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