METHOD AND SYSTEM FOR OPTIMIZING REINFORCEMENT-LEARNING-BASED AUTONOMOUS DRIVING ACCORDING TO USER PREFERENCES

摘要

A method and a system for optimizing reinforcement-learning-based autonomous driving according to user preferences are disclosed. A method for optimizing autonomous driving comprises the steps of: applying different autonomous driving parameters to a plurality of robot agents in a simulation through an automatic setting by means of the system or a direct setting by means of a manager, so that the robot agents learn robot autonomous driving; and optimizing the autonomous driving parameters by using preference data for the autonomous driving parameters.