Mitsubishi Electric has developed a proprietary deep-reinforcement algorithm for artificial-intelligence machine control that requires just one-fiftieth the number of trials compared to conventional AI control methods. The algorithm is expected to enable smart equipment such as industrial robots and vehicles to use sensors and cameras to rapidly learn about their environments for finely tuned AI-based control in unique environments. The algorithm reduces learning time: machines achieve extra-smart deep-reinforcement learning using sensor and camera data. This dramatically reduces number of trials and learning time compared to conventional deep-reinforcement learning methods that require extensive time to process huge amounts of data obtained from cameras and sensors, as well as extensive trials by machines using this data. The algorithm, combined with Mitsubishi Electric’s Compact AI technology released in February 2016, can be equipped in a wide range of machines. “The new algorithm – explains the company in a official note – requires just one-hundredth the amount of calculations compared to conventional methods. Machines with limited processing resources can use the solution to perform deep-reinforcement learning. Working in combination with Mitsubishi Electric’s Compact AI technology, the algorithm significantly reduces the calculation time compared to conventional methods, enabling deep-reinforcement learning to be deployed in a wide range of resource-limited equipment”.
