/DILP-Core

Python and TensorFlow implementation of the paper "Learning Explanatory Rules from Noisy Data." Evans Richard and Edward Grefenstette. Journal of Artificial Intelligence Research 61 (2018): 1-64.

Primary LanguageJupyter Notebook

Differentiable Inductive Logic Programming

Python and TensorFlow implementation of the paper "Learning Explanatory Rules from Noisy Data." Evans Richard and Edward Grefenstette. Journal of Artificial Intelligence Research 61 (2018): 1-64.

Paper: https://arxiv.org/pdf/1711.04574.pdf

DeepMind blog: https://deepmind.com/blog/learning-explanatory-rules-noisy-data/

To run the code you create a folder. In our case the folder example/. It has three files.

  • facts.ilp : contains the facts
  • negative.ilp: contains the negative examples
  • positive.ilp: contains the positive examples

You can run the code by:

python run.py example