... Abstract For the past few years, training robots to enable them to learn various manipulative skills using deep reinforcement learning (DRL) has arisen wide attention. However, large search space, low sample quality, and difficulties in network convergence pose great challenges to robot...

...), more and more scholars have begun to apply reinforcement learning (RL) and deep learning (DL) to solve practical problems. This paper focuses on the application of deep reinforcement learning (DRL) in the multi-robotic disassembly line balance problem (MRDLBP). In the MRDLBP problem, for each...