Special Issue on Probabilistic Logic Programming (PLP 2018)

Probabilistic logic programming (PLP) approaches have received much attention in this century. They address the need to reason about relational domains under uncertainty arising in a variety of application domains, such as bioinformatics, the semantic web, robotics, and many more. Developments in PLP include new languages that combine logic programming with probability theory as well as algorithms that operate over programs in these formalisms. By promoting probabilities as explicit programming constructs, inference, parameter estimation and learning algorithms can be run over programs which represent highly structured probability spaces. Following the Fifth Workshop on Probabilistic Logic Programming (PLP 2018), which was held on September 1, 2018, in Ferrara, Italy and co-located with the 28th International Conference on Inductive Logic Programming (ILP 2018), this Special Issue is devoted to all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.