Even if you are the only child, you should have the experience of grabbing toys and food with your cousins ​​as a child. It is really a good thing to think back now. Of course, if you grab something, you will lose and win. In addition, if you find it, you will better cope with the increase in the number of games and the understanding of the opponent's rules and routines. This is the innate ability of human beings to learn. .
Inspired by the developers of Google and Carnegie Mellon University, a machine learning algorithm was applied to the robot , so that it would be like "Zhou Botong", "both and right", grabbing each other through two robotic arms. To improve the crawling stability, it is very interesting.
The robot grabs a cylindrical object with one hand and grabs the other with one hand. Before the algorithm was loaded, basically the "aggressor" grabbed things very easily; after loading the algorithm and after a few trainings, the attacking robot actually failed, and the defender grabbed things more firmly. Prevent it from robbing.
Not only that, but the arm that has been exercised can grasp the object more stably when working independently. This is the purpose of this algorithm.
Lerrel Pinto, Ph.D., of the Carnegie Mellon University Robotics Institute, who is responsible for the project, said that this antagonistic algorithm helps robots achieve better self-learning and quickly adapt to new work environments and peers. This game-based insight algorithm uses deep learning techniques, and as time goes by, robots become smarter.
It seems that robots and AI have learned a human skill. We only hope that they don't start researching human weaknesses one day and then start fighting humans.
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