Google Brain's DRL Helps Robots 'Think While Moving' - Synced

When chasing a bouncing ball, a human will head where they anticipate the ball is going. If things change -- for example a cat swats the ball and it bounces off in a new direction -- the human will correct to an appropriate new route in real time. Robots can have a hard time making such changes, as they tend to simply observe states, then calculate and execute actions, rather than thinking while moving. Google Brain, UC Berkeley, and X Lab have proposed a concurrent Deep Reinforcement Learning (DRL) algorithm that enables robots to take a broader and more long-term view of tasks and behaviours, and decide on their next action before the current one is completed. The paper has been accepted by ICLR 2020.