Demonstration-Guided Multi-Objective Reinforcement Learning: Enhancing Exploration Efficiency and Policy Performance

This paper proposes a novel demonstration-guided multi-objective reinforcement learning (DG-MORL) algorithm that utilizes prior demonstrations to enhance exploration efficiency and policy performance in complex multi-objective reinforcement learning tasks.