Abstract

Abstract
We describe and compare design choices for meta-predicate semantics, as found in representative Prolog predicate-based module systems and in Logtalk. We look at the consequences of these design choices from a pragmatic perspective, discussing explicit qualification semantics, computational reflection support, expressiveness of meta-predicate directives, meta-predicate definitions safety, portability of meta-predicate definitions, and meta-predicate performance. We also describe how to extend the usefulness of meta-predicate definitions. Our aim is to provide useful insights to discuss meta-predicate semantics and portability issues based on actual implementations and common usage patterns. © 2012 Springer-Verlag.

Abstract

Abstract

Abstract

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.