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LoMRF is an open-source implementation ofMarkov Logic Networks (MLNs) written inScala programming language.

1. Parallel grounding algorithm based onAkka 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 producesAlchemy 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)

Latestdocumentation.

Contributions are welcome, for details seeCONTRIBUTING.md.

Copyright (c) 2014 - 2019 Anastasios Skarlatidis and Evangelos Michelioudakis

LoMRF is licensed under the Apache License, Version 2.0:https://www.apache.org/licenses/LICENSE-2.0

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

@misc{LoMRF,author = {Anastasios Skarlatidis and Evangelos Michelioudakis},title = {{Logical Markov Random Fields (LoMRF): an open-source implementation of Markov Logic Networks}},url = {https://github.com/anskarl/LoMRF},year = {2014}}