KG-A2C

March 3, 2020 ยท View on GitHub

Goal driven language generation using knowledge graph A2C agents. This code accompanies the paper Graph Constrained Reinforcement Learning for Natural Language Action Spaces.

Bibtex

@inproceedings{
ammanabrolu2020graph,
title={Graph Constrained Reinforcement Learning for Natural Language Action Spaces},
author={Prithviraj Ammanabrolu and Matthew Hausknecht},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://openreview.net/forum?id=B1x6w0EtwH}
}

Quickstart

Install Dependencies: Jericho, Redis, Pytorch >= 1.2

pip3 install --user jericho
pip3 install torch torchvision
sudo apt-get install redis-server

Download and extract Stanford CoreNLP then start the OpenIE server:

cd stanford-corenlp-full-2018-10-05/ && java -mx8g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -port 9000 -timeout 15000

Train KG-A2C

cd kga2c && python train.py --rom_file_path path_to_your_rom --openie_path path_to_your_openie_install --tsv_file ../data/rom_name_here