Guy Lever at Google DeepMind and his colleagues put battery-powered Robotis OP3 robots , which are about 50 centimetres tall and have 20 joints, through 240 hours of deep reinforcement learning.
This technique combines two key tenets of AI training: reinforcement learning sees agents gaining skills through trial and error, with a target of being rewarded for choosing correctly more often than choosing wrongly, while deep learning uses layers of neural networks – attempts to mimic the human brain – to analyse patterns within the data the AI is shown.
"The aim of this work isn’t to produce humanoid robots playing in the Premier League any time soon," says Aitken, "but rather to understand how we can build complex robot skills quickly, using synthetic training methodologies to build skills that can be rapidly, and more importantly robustly, transferred to real work applications."
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