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Authors: Luc de Raedt and Kristian Kersting
Article title: Bayesian Logic Programs
Publ. type: Article
Volume: 5
Article No: 34
Language: English
Abstract [en]: Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty. They are a probabilistic extension of propositional logic and, hence, inherit some of the limitations of propositional logic, such as the difficulties to represent objects and relations. The main contribution of this extended abstract is to introduce a new approach, called Bayesian logic programs, to overcome the limitations. It combines Bayesian networks with definite clause logic, i.e. "pure" Prolog, by establishing a one-to-one mapping between ground atoms and random variables. Thus, Bayesian logic programs combine the advantages of definite clause logic and Bayesian networks. This includes the separation of quantitative and qualitative aspects of the world. Furthermore, Bayesian logic programs generalize both Bayesian networks as well as logic programs, many ideas developed in both areas can be adapted.
Publisher: LINKÖPING University Electronic Press
Year: 2000
Available: 2000-12-21
No. of pages: 8
Series: LINKÖPING Electronic Articles in Computer and Information Science
ISSN: 1401-9841

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