This code is to accompany the paper Imitation Learning with Stability and Safety Guarantees. It learns a Neural Network controller with stability and safety guarantees through imitation learning process.

• He Yin (he_yin at berkeley.edu)
• Peter Seiler (pseiler at umich.edu)
• Ming Jin (jinming at vt.edu)
• Murat Arcak (arcak at berkeley.edu)

The code is written in Python3 and MATLAB.

There are several packages required:

• MOSEK: Commercial semidefinite programming solver
• CVX: MATLAB Software for Convex Programming
• Tensorflow: Open source machine learning platform

To plot the computed ROA, two more packages are required:

• SOSOPT: General SOS optimization utility
• Multipoly: Package used to represent multivariate polynomials

• To start the safe imitation learing process, go to each folder, run NN_policy.py. The computation results are stored in the folder data.
• To visualize the results for the inverted pendulum example, run result_analysis.m. For the GTM and vehicle lateral control examples, run plot_generation.m.