Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models | Zendy

Daan Fierens | Zendy; Hendrik Blockeel | Zendy; Maurice Bruynooghe | Zendy; Jan Ramon | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models

Author(s) -

Daan Fierens,

Hendrik Blockeel,

Maurice Bruynooghe,

Jan Ramon

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-28177-0

DOI - 10.1007/11536314_8

Subject(s) - probabilistic logic , bayesian network , computer science , relation (database) , artificial intelligence , bayesian probability , logical conjunction , machine learning , data mining , programming language

Acceptance rate: 51%Logical Bayesian Networks (LBNs) have recently been introduced as another language for knowledge based model construction of Bayesian networks, besides existing languages such as Probabilistic Relational Models (PRMs) and Bayesian Logic Programs (BLPs). The original description of LBNs introduces them as a variant of BLPs and discusses the differences with BLPs but still leaves room for a deeper discussion of the relationship between LBNs and BLPs. Also the relationship to PRMs was not treated in much detail.status: publishe

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research