Probabilistic logic programs (PLPs) define a set of probability distribution functions (PDFs) over the set of all Herbrand interpretations of the underlying logical language. When...
Matthias Broecheler, Gerardo I. Simari, V. S. Subr...
One of the advantages of logic programming is the fact that it offers many sources of implicit parallelism, such as and-parallelism and or-parallelism. Arguably, or-parallel system...
Modeling objects using formal grammars has recently regained much attention in computer vision. Probabilistic logic programming, such as Bilattice based Logical Reasoning (BLR), i...
Toufiq Parag, Claus Bahlmann, Vinay D. Shet, Manee...
ract interpretation of programs relates the exact semantics of a programming language to an approximate semantics that can be effectively computed. We show that, by specifying ope...
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...