ProbLog2: Probabilistic Logic Programming

被引：33

作者：

Dries, Anton ^{[1
]}

Kimmig, Angelika ^{[1
]}

Meert, Wannes ^{[1
]}

Renkens, Joris ^{[1
]}

Van den Broeck, Guy ^{[1
]}

Vlasselaer, Jonas ^{[1
]}

De Raedt, Luc ^{[1
]}

机构：

[1] Katholieke Univ Leuven, Leuven, Belgium

来源：

MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT III | 2015年 / 9286卷

关键词：

Probabilistic programming; Probabilistic inference; Parameter learning;

D O I：

10.1007/978-3-319-23461-8_37

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present ProbLog2, the state of the art implementation of the probabilistic programming language ProbLog. The ProbLog language allows the user to intuitively build programs that do not only encode complex interactions between a large sets of heterogenous components but also the inherent uncertainties that are present in real-life situations. The system provides efficient algorithms for querying such models as well as for learning their parameters from data. It is available as an online tool on the web and for download. The offline version offers both command line access to inference and learning and a Python library for building statistical relational learning applications from the system's components.

引用

页码：312 / 315

页数：4