Uniqueness of the Level Two Bayesian Network Representing a Probability Distribution
Bayesian Networks are graphic probabilistic models through which we can acquire, capitalize on, and exploit knowledge. they are becoming an important tool for research and applications in artificial intelligence and many other fields in the last decade. This paper presents Bayesian networks and disc...
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2011-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Online Access: | http://dx.doi.org/10.1155/2011/845398 |
| Summary: | Bayesian Networks are graphic probabilistic models through
which we can acquire, capitalize on, and exploit knowledge. they are becoming
an important tool for research and applications in artificial intelligence
and many other fields in the last decade. This paper presents
Bayesian networks and discusses the inference problem in such models. It
proposes a statement of the problem and the proposed method to compute
probability distributions. It also uses D-separation for simplifying
the computation of probabilities in Bayesian networks. Given a Bayesian
network over a family 𝐼 of random variables, this paper presents a result
on the computation of the probability distribution of a subset 𝑆 of 𝐼
using separately a computation algorithm and D-separation properties.
It also shows the uniqueness of the obtained result. |
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| ISSN: | 0161-1712 1687-0425 |