GGMMu

Utility function fitting using Generalized Gaussian Mixture Models (GGMM)

Prerequisites

• Python 3

Usage

python bell.py | cubic.py

Citation

Hadfi, Rafik, and Takayuki Ito. "Approximating Constraint-Based Utility Spaces Using Generalized Gaussian Mixture Models." International Conference on Principles and Practice of Multi-Agent Systems. Springer, Cham, 2014.

Licence & Copyright

This software was developed in the hope that it would be of some use to the AI research community, and is freely available for redistribution and/or modification under the terms of the GNU General Public Licence. It is distributed WITHOUT WARRANTY; without even the implied warranty of merchantability or fitness for a particular purpose. See the [GNU General Public License] for more details.

If you find this code to be of any use, please let me know. I would also welcome any feedback.

Copyright (c) 2015--2018 Rafik Hadfi, rafik.hadfi@gmail.com