  With the rapid development of deep learning, deep reinforcement learning
(DRL) began to appear in the field of resource scheduling in recent years.
Based on the previous research on DRL in the literature, we introduce online
resource scheduling algorithm DeepRM2 and the offline resource scheduling
algorithm DeepRM_Off. Compared with the state-of-the-art DRL algorithm DeepRM
and heuristic algorithms, our proposed algorithms have faster convergence speed
and better scheduling efficiency with regarding to average slowdown time, job
completion time and rewards.
