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ON DARWINIAN NETWORKS
被引:0
|作者:
Butz, Cory J.
[1
]
Oliveira, Jhonatan S.
[1
]
dos Santos, Andre E.
[1
]
机构:
[1] Univ Regina, Dept Comp Sci, Regina, SK S4S 2A0, Canada
基金:
加拿大自然科学与工程研究理事会;
关键词:
bayesian networks;
d-separation;
variable elimination;
join tree propagation;
D O I:
10.1111/coin.12101
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
We suggest Darwinian Networks (DNs) as a simplification of working with Bayesian networks (BNs). DNs adapt a handful of well-known concepts in biology into a single framework that is surprisingly simple yet remarkably robust. With respect to modeling, on one hand, DNs not only represent BNs but also faithfully represent the testing of independencies in a more straightforward fashion. On the other hand, with respect to three exact inference algorithms in BNs, DNs simplify each of them while unifying all of them. DNs can determine good elimination orderings using the same platform as used for modeling and inference. Finally, we demonstrate how DNs can represent two additional frameworks. Practical benefits of DNs include faster algorithms for inference and modeling.
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页码:629 / 655
页数:27
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