LoMRF

LoMRF is an open-source implementation of Markov Logic Networks.

View the Project on GitHub

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    Logical Markov Random Fields.

LoMRF: Logical Markov Random Fields

LoMRF is an open-source implementation of Markov Logic Networks (MLNs) written in Scala programming language.

Latest stable version LoMRF v0.6.0.

Features overview:

  1. Parallel grounding algorithm based on Akka Actors library.
  2. Marginal (MC-SAT) and MAP (MaxWalkSAT and LP-relaxed Integer Linear Programming) inference (lomrf infer).
  3. Batch and on-line Weight Learning (Max-Margin, AdaGrad and CDA) (lomrf wlearn).
  4. On-line Structure Learning (OSL and OSLa) (lomrf slearn).
  5. MLN knowledge base compilation (lomrf compile):
    • Predicate completion.
    • Clausal form transformation.
    • Replacement of functions with utility predicates and vice versa.
    • Reads and produces Alchemy compatible MLN files.
  6. Can export ground MRF in various formats (lomrf export).
  7. Can compare MLN theories (lomrf diff).
  8. Online supervision completion on semi-supervised training sets [currently experimental] (lomrf supervision).

Documentation

Documentation is available in LoMRF GitHub repository, as well as in lomrf.readthedocs.io (PDF, EPUB and HTML formats).

License

LoMRF comes with ABSOLUTELY NO WARRANTY. This is free software, and you are welcome to redistribute it under certain conditions; See the GNU Lesser General Public License v3 for more details.

Reference in Scientific Publications

Please use the following BibTex entry when you cite LoMRF in your papers:

@misc{LoMRF,
	author = {Anastasios Skarlatidis},
	title = ,
	url = {https://github.com/anskarl/LoMRF}
}