This folder contains the different toy examples presented in the paper "Learning from Demonstration with model-based Gaussian Processes" (N. Jaquier, D. Ginsbourger and S. Calinon), CoRL 2019.
These examples work with Python 2 and 3. First install the following packages:
pip install numpy
pip install matplotlib
pip install gpy (or https://github.com/SheffieldML/GPy)
The figures generated by the examples will be saved in the figures folder.
** GMR01 **
Example of GMR for 2-D outputs with time as input. Corresponds to Figure 1a of the main paper.
** GPR_coregionalization01 **
Example of multi-output GP for 2-D output with time as input. Corresponds to Figure 2b of the main paper.
** GMR_based_GPR01 **
Example of the GMR-based GP for 2-D outputs with time as input. Corresponds to Figure 2 of the main paper.
**GMR_based_GPR_uncertainty_examples01 **
Illustration of GMR-based GPR properties with 1-dimensional input and output. Corresponds to Figure 3 of the main paper. The user can change the number of observations, the lengthscale parameter and the noise variance in the file to generate different examples.