Declarative DeepProblog is a declarative extension to DeepProblog and all neuro-symbolic languages that rely on neural predicates.
This problem relies on deepproblog-dev (available from https://github.com/ML-KULeuven/deepproblog-dev), which provides a complete setup guide.
An implementation is also provided in the separate deepproblog.zip. Please follow the installation instructions.
This also includes the added predicates needed.
Please install the requirements.txt afterwards.
The experiments are sorted by their respective model, i.e. DeepProblog and DeepStochlog.
To run the declarative extension, navigate to any of the examples and run distr_generative.py.
Run python distr_generative.py --h to see all available options.
Two things are necessary:
- Encoder and decoder networks that map your entities into latent space (and back), and
- The DPL model formulation.