Darwinian Networks

Butz, Cory J.; Oliveira, Jhonatan S.; Santos, André E. dos

doi:10.1007/978-3-319-18356-5_2

Cited by 2 publications

(3 citation statements)

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“…Darwinian networks (DNs) [5,6] were proposed to simplify working with Bayesian networks (BNs) [7]. Rather than modeling the variables in a problem domain, DNs represent the probability tables in the model.…”

Section: Darwinian Networkmentioning

confidence: 99%

“…Furthermore, NoSQL databases are error tolerant. Darwinian networks (DNs) [5,6] are a probabilistic framework that can be used to simplify working with Bayesian networks (BNs) [7]. In DNs, a conditional probability table (CPT) is represented as a population.…”

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Representing Non-Relational Databases with Darwinian Networks

Andrade¹,

Teixeira²

2017

IJERA

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The Darwinian networks (DNs) are first introduced by Dr Butz [1] to simplify and clarify how to work with Bayesian networks (BNs). DNs can unify modeling and reasoning tasks into a single platform using the graphical manipulation of the probability tables that takes on a biological feel. From this view of the DNs, we propose a graphical library to represent and depict non-relational databases using DNs. Because of the growing of this kind of databases, we need even more tools to help in the management work, and the DNs can help with these tasks.

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Section: Darwinian Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Representing Non-Relational Databases with Darwinian Networks

Andrade¹,

Teixeira²

2017

IJERA

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On Darwinian Networks

Butz

Oliveira

Santos

2017

Computational Intelligence

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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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Darwinian Networks

Cited by 2 publications

References 12 publications

Representing Non-Relational Databases with Darwinian Networks

Representing Non-Relational Databases with Darwinian Networks

On Darwinian Networks

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