Reinforcement learning with multiple, potentially conflicting objectives is pervasive in real-
world applications, while this problem remains theoretically under-explored. This paper …

Learning an accurate value function for a given policy is a critical step in solving
reinforcement learning (RL) problems. So far, however, the convergence speed and sample …

In recent years, machine learning (ML) has achieved astonishing success in many areas,
including robotics, image recognition, natural language processing, and recommender …