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Robot has been widely used in a variety of fields, including grasping, transportation, welding. It is very precise and accurate. Grasping is the fundamental ability of the robot, which can determine the automatic level of the robot or the industry. Nowadays, the intelligent robot has become a very popular research field. This paper proposes the method of combining reinforcement learning and transfer learning, by training only once, and then slightly adjusting the neural network trained under similar environment or similar tasks, such as changing the number of layers or changing the action dimension, and then transferring to the new environment or tasks, so as to reduce the training time and improve efficiency.
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