Jaehun Han

Fast Adaptation of Deep Reinforcement Learning-Based Navigation Skills to Human Preference

Deep reinforcement learning (RL) is being actively studied for robot navigation due to its promise of superior performance and robustness. However, most existing deep RL navigation agents are trained using fixed parameters, such as maximum velocities and weightings of reward components. Since the op…