SKloeser / DRL4IOT

NLP DRL System for learning controls from JSON, XML and other data formats without manual pre-processing

DRL4IOT scap-2020-code-release

This is the supplemental material to the paper "DRL for IoT Interoperability" found on: https://www.researchgate.net/publication/341641724_Deep_Reinforcement_Learning_for_IoT_Interoperability

Setup

Follow these steps to setup the repository:

1. Create a new virtual env using python 3.6
2. Install requirements:
   pip install -r requirements.txt
3. Install NLTK data:
   python -c "import nltk; nltk.download('punkt')"
4. Download GloVe pre-trained word vectors and extract in weights directory:
   Linux:
   wget -c http://nlp.stanford.edu/data/wordvecs/glove.6B.zip -P weights
unzip weights/glove.6B.zip -d weights

Model training

Step by Step training example can be found in Training.ipynb notebook.