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.
- Project Page: http://www.actioncores.org
- Lead developer: Daniel Nyga (nyga@cs.uni-bremen.de)
- Contributors: Mareike Picklum (mareikep@cs.uni-bremen.de)
- Version 1.0.0 (19.12.2017)
- Release: Initial release
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