https://github.com/tsudalab/mdts

Materials Design by Monte Carlo Tree Search
https://github.com/tsudalab/mdts

machine-learning materials-design python-library

Last synced: about 1 month ago
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Materials Design by Monte Carlo Tree Search

• Host: GitHub
• URL: https://github.com/tsudalab/mdts
• Owner: tsudalab
• Created: 2017-03-22T04:03:56.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2021-12-02T09:52:53.000Z (about 3 years ago)
• Last Synced: 2023-10-20T23:33:29.577Z (about 1 year ago)
• Topics: machine-learning, materials-design, python-library
• Language: Python
• Homepage:
• Size: 772 KB
• Stars: 31
• Watchers: 10
• Forks: 10
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# MDTS

Materials Design by Monte Carlo Tree Search

# Required Packages

Python >= 2.7.x (Python 3. also can be used)

numpy >=1.12.x

COMBO  (if you want to use Bayesian optimzation in combination with MDTS)

https://github.com/tsudalab/combo3

Tensorflow 2 and Keras if you want to use the neural network expansion policy in combination with MDTS

# Documentation

Complete documentation is [here](http://mdts.readthedocs.io/en/latest/)

# Installation

Download or clone the github repository, e.g.

git clone https://github.com/tsudalab/MDTS

CD to the MDTS folder

python setup.py install

Please refer to test.py file for usage

# Contact

Sae Dieb: [email protected]

If you use this package, please cite us:

Thaer M. Dieb, Shenghong Ju, Kazuki Yoshizoe, Zhufeng Hou, Junichiro Shiomi and Koji Tsuda,

MDTS: Automatic Complex Materials Design using Monte Carlo Tree Search,

Science and Technology of Advanced Materials, Vol. 18, Iss. 1, 2017