On the Implementation of the CLP(BN) Language

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

Vitor Santos Costa (Author) FCUP

Conference proceedings International

Title: PRACTICAL ASPECTS OF DECLARATIVE LANGUAGES, PROCEEDINGS

Pages: 234-248

12th International Symposium on Practical Aspects of Declarative Languages

Madrid, SPAIN, JAN 18-19, 2010

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 2 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-003-CBN

DOI: 10.1007/978-3-642-11503-5_20

Abstract (EN): The last few years have seen great interest in developing models that can describe real-life large-scale structured systems. A popular approach is to address these problems by using logic to describe the patterns or structure of the problems, and by using a calculus of probabilities to address the uncertainty so often found in real life situations. The CLP(BN) language is an extension of Prolog that allows the representation, inference, and learning of bayesian networks. The language was inspired on Koller's Probabilistic Relational Models, and is close to other probabilistic relational languages based in Prolog, such as Sato's PRISM. We present the implementation of CLP(BN), showing how bayesian networks are represented in CLP(BN) and presenting the implementation of three different inference algorithms: Gibbs Sampling, Variable Elimination, and Junction Trees. We show that these algorithms can be implemented effectively by using a matrix library and a graph manipulation library, and study how the system performs on real-life applications.

Language: English

Type (Professor's evaluation): Scientific

Notes: ISBN: 978-3-642-11502-8. - Editors Manuel Carro and Ricardo Peña. - Publisher: Springer

No. of pages: 15