LoMRF

LoMRF is an open-source implementation of Markov Logic Networks

Programming language: Scala

License: Apache License 2.0

Tags: Science And Data Analysis    

Latest version: v0.7.1

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}
}