Awesome

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LoMRF: Logical Markov Random Fields

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

Features overview:

Parallel grounding algorithm based on Akka Actors library.
Marginal (MC-SAT) and MAP (MaxWalkSAT and LP-relaxed Integer Linear Programming) inference (lomrf infer).
Batch and on-line Weight Learning (Max-Margin, AdaGrad and CDA) (lomrf wlearn).
On-line Structure Learning (OSL and OSLa) (lomrf slearn).
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.

Can export ground MRF in various formats (lomrf export).
Can compare MLN theories (lomrf diff).
Online supervision completion on semi-supervised training sets [currently experimental] (lomrf supervision)

Documentation

Latest documentation.

Contributions

Contributions are welcome, for details see CONTRIBUTING.md.

License

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

Reference in Scientific Publications

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}
}