/Neural-Symbolic-Learner

Primary LanguageJupyter Notebook

Neural-Symbolic Learner for Michalski's train problem

  • open and run Neural_Symbolic_Learner.ipynb on google colab or localy with jupyter notebook
    • the main dependencies are shown on the first cell to be run. It installs tensorflow, keras and other modules that are used in the notebook.
    • run all cells to get the result. It may take a while (estimated time: 2 hours).

Michalski’s train details

  • The problem:

    • there are ten railway trains;
    • five are travelling east;
    • five are travelling west;
    • each train comprises a locomotive pulling wagons;

  • Whether a particular train is travelling towards the east or towards the west is determined by some properties of that train:

    • appended wagons;
    • short or long wagons;
    • closed or open wagons;
    • jagged or not;
    • shaped the wagons contain;
    • how many shapes;
    • and more.

  • The data describes different features of trains. The positive examples are the trains on the left in the figure below and the negative examples are the trains on the right:

Fig. 1[Fig. 1]

The task of the learner is to find characteristics that determine the direction the train take.