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Programming language: Scala
Latest version: v0.7.1

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README

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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.
  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

Latest [documentation](docs/index.md).

Contributions

Contributions are welcome, for details see [CONTRIBUTING.md](CONTRIBUTING.md).

License

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

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}
}


*Note that all licence references and agreements mentioned in the LoMRF README section above are relevant to that project's source code only.