LPMLN is a recent addition to probabilistic logic programming languages. Its main idea is to assign weights to stable models in a way similar to Markov Logic assigns weights to models.
LPMLN v1.0 includes two implementations of LPMLN. The first one, called lpmln2asp, compiles LPMLN into the input language of clingo utilizing weak constraints. The second one, called lpmln2mln, compiles LPMLN into the input language of Markov Logic implementations like Alchemy, Tuffy and Rockit.
This webpage only includes the tutorials for LPMLN v1.0. The package and tutorials for LPMLN v1.1 are available at our Github page: https://github.com/azreasoners/lpmln