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JACIII Vol.8 No.2 pp. 93-99
doi: 10.20965/jaciii.2004.p0093
(2004)

Review:

Bayesian Network: Probabilistic Reasoning, Statistical Learning, and Applications

Yoichi Motomura

National Institute of Advanced Industrial Science and Technology, 2-41-6 Aomi, Koto-ku, Tokyo 135-0064, Japan

Received:
September 18, 2003
Accepted:
December 1, 2003
Published:
March 20, 2004
Keywords:
Bayesian network, probabilistic reasoning, statistical learning, intelligent system, probabilistic model
Abstract

Bayesian networks are probabilistic models that can be used for prediction and decision-making in the presence of uncertainty. For intelligent information processing, probabilistic reasoning based on Bayesian networks can be used to cope with uncertainty in real-world domains. In order to apply this, we need appropriate models and statistical learning methods to obtain models. We start by reviewing Bayesian network models, probabilistic reasoning, statistical learning, and related researches. Then, we introduce applications for intelligent information processing using Bayesian networks.

Cite this article as:
Yoichi Motomura, “Bayesian Network: Probabilistic Reasoning, Statistical Learning, and Applications,” J. Adv. Comput. Intell. Intell. Inform., Vol.8, No.2, pp. 93-99, 2004.
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Last updated on Oct. 15, 2021