@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",

}