@inproceedings{53cd38fb2e9d439396ae1ec5224bc882,
title = "The complexity of inferences and explanations in probabilistic logic programming",
abstract = "{\textcopyright} Springer International Publishing AG 2017. A popular family of probabilistic logic programming languages combines logic programs with independent probabilistic facts. We study the complexity of marginal inference, most probable explanations, and maximum a posteriori calculations for propositional/relational probabilistic logic programs that are acyclic/definite/stratified/normal/ disjunctive. We show that complexity classes Σk and PPΣk (for various values of k) and NPPP are all reached by such computations.",
author = "Cozman, {Fabio G.} and Mau{\'a}, {Denis D.}",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-61581-3_40",
language = "American English",
isbn = "9783319615806",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "449--458",
booktitle = "The complexity of inferences and explanations in probabilistic logic programming",
note = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Conference date: 01-01-2018",
}