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Probabilistic Action Cores (PRAC) - Natural-language Understanding for Technical Cognitive Systems

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PRAC -- Probabilistic Robot Action Cores

Knowledge about actions and objects is represented as Probabilistic Robot Action Cores (PRAC), which can be thought of as generic event patterns that enable a robot to infer important information that is missing in an original natural-language instruction. PRAC models are represented in Markov Logic Networks, a powerful knowlegde represenation formalism combining first-order logic and probability theory.

Release notes

  • Version 1.0.0 (19.12.2017)
    • Release: Initial release

Documentation

PRAC comes with its own sphinx-based documentation. To build it, conduct the following actions:

$ cd path/to/prac/doc
$ make html

If you have installed Sphinx, the documentation should be build. Open it in your favorite web browser:

$ firefox _build/html/index.html

Sphinx can be installed with

$ sudo pip install sphinx sphinxcontrib-bibtex

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