Nikos Aréchiga

A Safe Preference Learning Approach for Personalization With Applications to Autonomous Vehicles

This letter introduces a preference learning method that ensures adherence to given specifications, with an application to autonomous vehicles. Our approach incorporates the priority ordering of Signal Temporal Logic (STL) formulas describing traffic rules into a learning framework. By leveraging Pa