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

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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.

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.
  1. Can export ground MRF in various formats (lomrf export).
  2. Can compare MLN theories (lomrf diff).
  3. 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

Copyright (c) 2014 - 2018 Anastasios Skarlatidis and Evangelos Michelioudakis

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}
}