Under Consideration for Publication in Theory and Practice of Logic Programming on the Implementation of the Probabilistic Logic Programming Language Problog
By Angelika Kimmig, Bart Demoen, Bart Demoen, Luc De Raedt, Luc De Raedt, Vítor Santos Costa, Vítor Santos Costa, Ricardo Rocha
5 citations recorded by the source corpus.
Abstract The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In ProbLog, facts can be labeled with probabilities. These facts are treated as mutually independent random variables that indicate whether these facts belong to a randomly sampled program. Different kinds of queries can be posed to ProbLog programs. We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system, and evaluate their performance in the context of large networks of biological entities.
Subfields: Artificial Intelligence, Computer Networks and Communications, Probabilistic & Bayesian Methods
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Frank D. Wood
- Hongseok Yang
- Jan-Willem van de Meent
- Brooks Paige
- Yura N. Perov
- David Tolpin
- Zoubin Ghahramani
- Tom Rainforth
In Computer Networks and Communications
In Probabilistic & Bayesian Methods
- Frank D. Wood
- Hongseok Yang
- Jan-Willem van de Meent
- Brooks Paige
- Yura N. Perov
- David Tolpin
- Zoubin Ghahramani
- Tom Rainforth
Citations in the corpus
- An Introduction to Probabilistic Programming (2018, background): “We have left off of the preceding extensive list of languages both one important class of language – probabilistic logic languages ((Kimmig et al., 2011),(Sato and Kameya, 1997) – and sophisticated, useful, and widely deployed libraries/embedded domain-specific languages for modeling and inference (”