Utility function fitting using Generalized Gaussian Mixture Models (GGMM)
- Python 3
python bell.py
python cubic.py
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.
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